{"as_of":"2026-08-05T07:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d8e9acfe58a912876e63f9aee365b05fa0ec1bacea57b1037d00416e74638712","coverage":[{"denominator":110,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-19T16:46:56.743268Z","state":"measured"},{"denominator":105,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":105,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-01T07:04:06.161855Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"cited_work":{"arxiv_id":"2604.08302","doi":"10.48550/arxiv.2604.08302","metadata_source":"pith","pith_arxiv_id":"2604.08302","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","venue":"cs.LG","work_id":"3b4ffacd-f9f2-4ce1-952d-12a9b4425b27","year":2026},"citing_paper":{"arxiv_id":"2605.30876","last_updated":"2026-06-20T08:46:49Z","snapshot_observed_at":"2026-08-03T23:34:59.657375Z","submitted_at":"2026-05-29T06:03:50Z","title":"dMoE: dLLMs with Learnable Block Experts","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-06-28T22:50:51.900169Z"},"links":{"cited_paper":"/paper/2604.08302","citing_paper":"/paper/2605.30876"},"observation_digest":"sha256:afb7157fcac28266861e6d25f3ff5f7ff7bd791cf28839f595587ce35c73ba68","observation_id":"284a7712-27d3-41e7-8778-07cb93c37838","resolution":{"observed_at":"2026-06-28T22:52:45.153989Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"cited_work":{"arxiv_id":"2604.08302","doi":"10.48550/arxiv.2604.08302","metadata_source":"pith","pith_arxiv_id":"2604.08302","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","venue":"cs.LG","work_id":"3b4ffacd-f9f2-4ce1-952d-12a9b4425b27","year":2026},"citing_paper":{"arxiv_id":"2606.08810","last_updated":"2026-06-15T19:27:43Z","snapshot_observed_at":"2026-08-02T08:52:28.875995Z","submitted_at":"2026-06-07T20:00:33Z","title":"Continuous Language Diffusion as a Decoder-Interface Problem","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T18:27:10.422343Z"},"links":{"cited_paper":"/paper/2604.08302","citing_paper":"/paper/2606.08810"},"observation_digest":"sha256:7b3f1a6a0586ce1e9d77ba9525c7fd73eab3cc0d7d162cc7f477f65296472c5b","observation_id":"24ef571f-d319-4e39-bf4b-70d92b7e5af1","resolution":{"observed_at":"2026-06-27T18:31:07.709919Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"cited_work":{"arxiv_id":"2604.08302","doi":"10.48550/arxiv.2604.08302","metadata_source":"pith","pith_arxiv_id":"2604.08302","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","venue":"cs.LG","work_id":"3b4ffacd-f9f2-4ce1-952d-12a9b4425b27","year":2026},"citing_paper":{"arxiv_id":"2606.12232","last_updated":"2026-06-10T15:41:26Z","snapshot_observed_at":"2026-07-06T23:51:13.191639Z","submitted_at":"2026-06-10T15:41:26Z","title":"Re-evaluating Confidence Remasking in Masked Diffusion Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T10:25:09.995616Z"},"links":{"cited_paper":"/paper/2604.08302","citing_paper":"/paper/2606.12232"},"observation_digest":"sha256:e99c1deb39a945372563f1a25df944021a4859bba236fb23ccb2234482bfafe0","observation_id":"2ec974eb-81ec-4871-9095-a1e4ad9c6b57","resolution":{"observed_at":"2026-07-03T09:17:48.806236Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"cited_work":{"arxiv_id":"2604.08302","doi":"10.48550/arxiv.2604.08302","metadata_source":"pith","pith_arxiv_id":"2604.08302","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","venue":"cs.LG","work_id":"3b4ffacd-f9f2-4ce1-952d-12a9b4425b27","year":2026},"citing_paper":{"arxiv_id":"2606.29215","last_updated":"2026-06-30T11:21:37Z","snapshot_observed_at":"2026-08-03T18:17:11.319044Z","submitted_at":"2026-06-28T05:53:45Z","title":"Multi-Block Diffusion Language Models","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-06-30T08:53:31.494892Z"},"links":{"cited_paper":"/paper/2604.08302","citing_paper":"/paper/2606.29215"},"observation_digest":"sha256:da9d2237789b0f84b4cf0f7649e1556ae868ebb3f3a3b70a68496b29ac9048cb","observation_id":"78216845-bb41-413f-a6f3-63cd87cbf606","resolution":{"observed_at":"2026-06-30T08:54:29.541466Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"cited_work":{"arxiv_id":"2604.08302","doi":"10.48550/arxiv.2604.08302","metadata_source":"pith","pith_arxiv_id":"2604.08302","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","venue":"cs.LG","work_id":"3b4ffacd-f9f2-4ce1-952d-12a9b4425b27","year":2026},"citing_paper":{"arxiv_id":"2606.29215","last_updated":"2026-06-30T11:21:37Z","snapshot_observed_at":"2026-08-03T18:17:11.319044Z","submitted_at":"2026-06-28T05:53:45Z","title":"Multi-Block Diffusion Language Models","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-01T07:04:06.161855Z"},"links":{"cited_paper":"/paper/2604.08302","citing_paper":"/paper/2606.29215"},"observation_digest":"sha256:5f6bb71253d7e19326e917b84d9c180c399ebc313a7788c37f60d02a4a26e8bb","observation_id":"0857fd2d-811e-491c-a9f5-6cf3a83b66e5","resolution":{"observed_at":"2026-07-01T07:05:28.323711Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2604.08302/citation-record","integrity":"/paper/2604.08302/integrity","json":"/paper/2604.08302/citation-record.json","paper":"/paper/2604.08302"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":"2303.08774","doi":"10.1002/tea.20265","metadata_source":"pith","pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4 Technical Report","venue":"cs.CL","work_id":"b928e041-6991-4c08-8c81-0359e4097c7b","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c31c349833258d8e62573373115d4bca86324d94759cce156b13c26e79c8e0fa","observation_id":"bc375e90-838c-44b0-807d-fc9fe95d4085","resolution":{"observed_at":"2026-05-19T16:47:40.146952Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.04030","last_updated":"2025-08-07T23:16:09Z","snapshot_observed_at":"2026-07-06T21:04:43.010093Z","submitted_at":"2025-04-05T02:52:16Z","title":"OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs","version":2},"cited_work":{"arxiv_id":"2504.04030","doi":"10.48550/arxiv.2504.04030","metadata_source":"arxiv_reference","pith_arxiv_id":"2504.04030","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"OpenCodeInstruct: A large-scale instruction tuning dataset for code LLMs.arXiv preprint","venue":"ArXiv.org","work_id":"136700a7-11f6-48b3-8b28-1be2840954e9","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2504.04030","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:103c0f5900e2165faff02ff1c2ae19a8825cdf55a0ad44f3ff80cccf510211e1","observation_id":"f9d0ae2f-014c-4052-8f73-2f37f5475b6e","resolution":{"observed_at":"2026-05-19T16:47:40.144387Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09573","last_updated":"2025-05-17T21:15:02Z","snapshot_observed_at":"2026-08-03T23:49:05.512328Z","submitted_at":"2025-03-12T17:43:40Z","title":"Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models","version":3},"cited_work":{"arxiv_id":"2503.09573","doi":"10.48550/arxiv.2503.09573","metadata_source":"pith","pith_arxiv_id":"2503.09573","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models","venue":"cs.LG","work_id":"b34ab928-6ffb-4028-b13c-395a8924d76b","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2503.09573","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:da922ab59653a6a4a36555a31cf9cd9cc6b7cccd452c249c5af8a879df5fffdc","observation_id":"823b42af-7b71-47e1-a1f3-98a013338578","resolution":{"observed_at":"2026-05-19T16:47:40.180455Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T08:26:05.754154Z","title":"Structured denoising diffusion models in discrete state-spaces.Advances in neural information processing systems, 34:17981–17993","venue":null,"work_id":"b3c340e2-b557-4352-95ba-6967124a292d","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:8869cf20962ab8e1c932a4e1380703b0f1511636289ed28744e92ce3580cfb6f","observation_id":"22983622-7ba9-4f05-95c5-38868c285779","resolution":{"observed_at":"2026-05-19T16:47:40.647327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07732","last_updated":"2021-08-16T03:57:30Z","snapshot_observed_at":"2026-08-02T19:23:53.535075Z","submitted_at":"2021-08-16T03:57:30Z","title":"Program Synthesis with Large Language Models","version":1},"cited_work":{"arxiv_id":"2108.07732","doi":"10.1007/s11390-025-5518-5","metadata_source":"pith","pith_arxiv_id":"2108.07732","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Program Synthesis with Large Language Models","venue":"cs.PL","work_id":"fd241a05-03b9-4de2-9588-9d77ce176125","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2108.07732","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f6ef61f9af34928d144c314c15dc8953709954477dd62cb02a3fe3de30722309","observation_id":"27a810ea-e4b2-4a15-8884-3abfc3f14360","resolution":{"observed_at":"2026-05-19T16:47:40.152687Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16609","last_updated":"2023-09-28T17:07:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-28T17:07:49Z","title":"Qwen Technical Report","version":1},"cited_work":{"arxiv_id":"2309.16609","doi":"10.48550/arxiv.2309.16609","metadata_source":"pith","pith_arxiv_id":"2309.16609","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen Technical Report","venue":"cs.CL","work_id":"bb1fd52f-6b2f-437c-9516-37bdf6eb9be8","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2309.16609","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:6c80ef2deaf8a5e468419ae672b523ba6f5997324170e7256e8426e2e16a2ee2","observation_id":"dd4dcea7-acdf-460f-849e-d28c98beb5ad","resolution":{"observed_at":"2026-05-19T16:47:40.141516Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-15T23:50:15.620681+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-15T23:50:15.620681+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning to parallel: Accelerating diffusion large language models via adaptive parallel decoding","venue":null,"work_id":"51aef6dc-1c5a-49b1-90ae-b1f44460a3f7","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:b5c5b8fb603b5d6b7e36d32f1cd0cb890c040ea73217780d1bffa860a4857761","observation_id":"fd6305b5-83c8-437d-a90e-3d22bd6eb709","resolution":{"observed_at":"2026-05-19T16:47:40.645279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.24857","last_updated":"2025-05-30T17:52:55Z","snapshot_observed_at":"2026-07-06T21:33:50.814913Z","submitted_at":"2025-05-30T17:52:55Z","title":"Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking","version":1},"cited_work":{"arxiv_id":"2505.24857","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.24857","snapshot_observed_at":"2026-07-01T23:36:23.363394Z","title":"Accelerated sampling from masked diffusion models via entropy bounded unmasking","venue":null,"work_id":"87f3b449-ac69-40f1-a330-34d31ccfba8e","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.24857","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:9a79b700b33f2987fedc6a7933dd061c411d1ddc0a33f778ef3ab7d12d00b5b4","observation_id":"034efed6-7778-4103-8bf2-5a1d336b0f98","resolution":{"observed_at":"2026-05-19T16:47:40.139007Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.08676","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T03:07:52.049493Z","title":"LLaDA2.1 : Speeding up text diffusion via token editing","venue":null,"work_id":"e3c404e2-a097-4443-8acd-3b073ce2156e","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:0eb03625be085818fe2528e057a7349cda5a18c7eedc70edead3419582193137","observation_id":"61efc888-300e-4536-b175-fc66e0ed79a2","resolution":{"observed_at":"2026-05-19T16:47:40.085239Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.15745","last_updated":"2025-12-24T03:46:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-10T09:26:18Z","title":"LLaDA2.0: Scaling Up Diffusion Language Models to 100B","version":2},"cited_work":{"arxiv_id":"2512.15745","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.15745","snapshot_observed_at":"2026-07-11T03:07:51.909523Z","title":"LLaDA2.0: Scaling Up Diffusion Language Models to 100B","venue":"cs.LG","work_id":"a1b1080d-0a91-44a4-8f70-2bf3e7a27e0b","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2512.15745","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:8f9d4efef0145099104b4245816f55bbcb4aac5daa00a036cb7171201a62844e","observation_id":"12594179-ddca-4ec0-967c-e0fa93041e18","resolution":{"observed_at":"2026-05-19T16:47:40.076018Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10774","last_updated":"2024-06-14T23:32:32Z","snapshot_observed_at":"2026-07-06T17:17:56.276857Z","submitted_at":"2024-01-19T15:48:40Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","version":3},"cited_work":{"arxiv_id":"2401.10774","doi":"10.48550/arxiv.2401.10774","metadata_source":"pith","pith_arxiv_id":"2401.10774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","venue":"cs.LG","work_id":"f6202cd1-1a78-4c19-8242-688acf4952b6","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2401.10774","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c428401fb076e48d909c91034c8086e6fe10311b108d74ce26072e7d532d5398","observation_id":"c0b2c502-5ed8-48a1-97af-93e267948b74","resolution":{"observed_at":"2026-05-19T16:47:40.222884Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2602.06036","last_updated":"2026-05-28T09:13:25Z","snapshot_observed_at":"2026-08-03T04:09:50.707111Z","submitted_at":"2026-02-05T18:59:30Z","title":"DFlash: Block Diffusion for Flash Speculative Decoding","version":2},"cited_work":{"arxiv_id":"2602.06036","doi":"10.48550/arxiv.2602.06036","metadata_source":"pith","pith_arxiv_id":"2602.06036","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2602.06036 , year=","venue":"cs.CL","work_id":"860ff726-6feb-4917-a25f-95159b43dd49","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2602.06036","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:73fe26473756f4fd7f8b88a7a43136d52fd6beec7262586c3108ac10d50328a4","observation_id":"2795d43c-923d-4695-a550-86ccfd0950db","resolution":{"observed_at":"2026-05-29T02:05:01.756664Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9da42e83-8197-49b8-95d8-bb472a6076b1","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f012f0cbe495fb8bb345174858737f7fb9b2451b154fb143b4138bc86a4333dd","observation_id":"6f64a1ed-9968-44af-9e98-b825dd223b09","resolution":{"observed_at":"2026-05-19T16:47:40.653588Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.21446","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T08:53:16.304279Z","title":"dultra: Ultra-fast diffusion language models via reinforcement learning","venue":null,"work_id":"ff9c1049-4b9b-4c61-9de6-85407d92de4c","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:7aaff6de9f643e38cbe5ebdf0dd2c7155476fde781bb3ed86f771bcdd456e77b","observation_id":"dfbfce57-59a2-4720-b462-ca44b34ba765","resolution":{"observed_at":"2026-05-19T16:47:40.220367Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.14148","last_updated":"2025-08-23T20:28:45Z","snapshot_observed_at":"2026-07-06T22:15:12.721846Z","submitted_at":"2025-08-19T16:56:51Z","title":"DPad: Efficient Diffusion Language Models with Suffix Dropout","version":2},"cited_work":{"arxiv_id":"2508.14148","doi":"10.48550/arxiv.2508.14148","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.14148","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Dpad: Efficient diffusion language models with suffix dropout.arXiv preprint arXiv:2508.14148","venue":"ArXiv.org","work_id":"3f0e3292-b812-4d35-9383-8e3959725c6b","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.14148","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:4e69c23ea24aeafe29808d143ff9f29b5512ea13712d438b283f3b0e4d4e86fb","observation_id":"f5a25185-7b8d-482d-ba72-d1cb68246ad9","resolution":{"observed_at":"2026-05-19T16:47:40.008037Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.26488","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T23:36:23.374635Z","title":"dparallel: Learnable parallel decoding for dllms","venue":null,"work_id":"92d4d572-3089-4267-aa76-3c257ab6e6ad","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:ccbc2000da41046d8fbfee1a5ceff8b98e09a9c3765c7be5dd84b310e5793c54","observation_id":"4ef4e79c-8d22-414d-bcc4-7cf340d92ee1","resolution":{"observed_at":"2026-05-19T16:47:40.002769Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.06303","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T03:07:51.378138Z","title":"Sdar: A syn- ergistic diffusion-autoregression paradigm for scalable sequence generation.arXiv preprint arXiv:2510.06303","venue":null,"work_id":"78561109-9df2-4b95-b2c6-4136d3384b98","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:067d767d87c554c03905140c1c70aa17238238b27f6aa140a24857fd9e1ca966","observation_id":"68cdd249-e992-4e3d-8f15-2ea6601e5713","resolution":{"observed_at":"2026-05-19T16:47:40.214425Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.14068","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sdar-vl: Stable and efficient block-wise diffusion for vision-language understanding","venue":null,"work_id":"a98ca05a-4215-477c-abf2-586c8f9d737c","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:b30f5f587739f2ebe32b8ba1afb48b2757b0dc7fdf791355976246e721f965b9","observation_id":"f4f84bad-02a5-4be8-bf95-8d9358553ca6","resolution":{"observed_at":"2026-05-19T16:47:40.217604Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.20604","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Moe-diffuseq: Enhancing long-document diffusion models with sparse attention and mixture of experts","venue":null,"work_id":"853f6e3d-ee7d-4568-bb54-4976f502786d","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:fb42cf44cf13079ef48a5968d675a705a9778dbf23163d04311a8ccc48ae9eed","observation_id":"abad22b0-40f1-45d1-b250-82f32d24f0bd","resolution":{"observed_at":"2026-05-19T16:47:40.226261Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-04T15:46:25.710484Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":"2110.14168","doi":"10.1002/j.1545-","metadata_source":"pith","pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Training Verifiers to Solve Math Word Problems","venue":"cs.LG","work_id":"acab1aa8-b4d6-40e0-a3ee-25341701dca2","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:7a05517f4513673c79fe1a7a68301d37ad749cde34cb539b038fac9bbfea5307","observation_id":"d02f8cf2-e50d-48fa-871b-6f4f08ec98f6","resolution":{"observed_at":"2026-05-19T16:47:40.232356Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.15892","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Stable-diffcoder: Pushing the frontier of code diffusion large language model","venue":null,"work_id":"82e1edfc-1d6e-4d0e-a2c8-1844227818e9","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:dc87b10a96d4ca70f90eafff2343153e4de1fe8e866b3a4f1b2ee6de77f99f21","observation_id":"b3728b1c-cefc-4c81-844c-784fbe3ad33d","resolution":{"observed_at":"2026-05-19T16:47:40.247587Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.12153","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T22:52:45.050589Z","title":"dvoting: Fast voting for dllms","venue":null,"work_id":"3f3f9a94-8a19-4a7b-bd29-42b8764a1717","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:aa983d1d305ce49333fdac07e5e89579b0eab07737a6d361f20b823ed254a052","observation_id":"985cbeea-039b-46fc-95c3-a3c4ac9d128c","resolution":{"observed_at":"2026-05-19T16:47:40.265104Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.14067","last_updated":"2026-04-29T20:52:08Z","snapshot_observed_at":"2026-07-06T22:39:08.850289Z","submitted_at":"2025-12-16T04:12:17Z","title":"Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed","version":2},"cited_work":{"arxiv_id":"2512.14067","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.14067","snapshot_observed_at":"2026-07-11T03:07:51.162396Z","title":"Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed","venue":"cs.CL","work_id":"df68a164-2dfd-4559-984e-6095ef320eed","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2512.14067","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:23c76559a0e4e604a16d239901ddd24d333155b2c45b29f1586aa7ccd01f3408","observation_id":"449d9b1a-8d8e-4b56-b772-8622d4e69305","resolution":{"observed_at":"2026-05-19T16:47:40.197686Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20639","last_updated":"2025-06-26T15:46:40Z","snapshot_observed_at":"2026-08-01T20:24:21.885586Z","submitted_at":"2025-06-25T17:35:47Z","title":"DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation","version":2},"cited_work":{"arxiv_id":"2506.20639","doi":"10.48550/arxiv.2506.20639","metadata_source":"pith","pith_arxiv_id":"2506.20639","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Diffu- coder: Understanding and improving masked diffusion mod- els for code generation.arXiv preprint arXiv:2506.20639","venue":"cs.CL","work_id":"174cb4e5-25ae-4cca-b4e2-405cbd5774ba","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2506.20639","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:6461bae75cc82309043238e9467e44d9ba6c44c636ccb5d21edbf54adb9c87c5","observation_id":"6c45b0c2-2c19-41da-b8fc-74005817c17d","resolution":{"observed_at":"2026-05-19T16:47:40.189153Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":"2407.21783","doi":"10.1016/s0749-0720(15","metadata_source":"pith","pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"The Llama 3 Herd of Models","venue":"cs.AI","work_id":"1549a635-88af-4ac1-acfe-51ae7bb53345","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:3a52ea62f0efba315eadc03e37240f8cd8997392818c6b6417c75e3147ee54f9","observation_id":"4a70bbc3-746a-438a-9097-2cb8da968420","resolution":{"observed_at":"2026-05-19T16:47:40.191737Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.04178","last_updated":"2025-06-05T02:21:52Z","snapshot_observed_at":"2026-08-03T02:41:13.331563Z","submitted_at":"2025-06-04T17:25:39Z","title":"OpenThoughts: Data Recipes for Reasoning Models","version":2},"cited_work":{"arxiv_id":"2506.04178","doi":"10.48550/arxiv.2506.04178","metadata_source":"pith","pith_arxiv_id":"2506.04178","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"OpenThoughts: Data Recipes for Reasoning Models","venue":"cs.LG","work_id":"c7acbe41-27a0-4773-a7be-8f08d86cdf21","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2506.04178","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:b49d067eb39ff45b844b1924ee8e1a5c9ddfad8931e1d1879cfa74c99b490510","observation_id":"930e08ba-f323-4360-9741-96647dbf8478","resolution":{"observed_at":"2026-05-19T16:47:40.194913Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-23T10:52:48.169741+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T10:52:48.169741+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.00707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reward-weighted sampling: Enhancing non-autoregressive characteristics in masked diffusion llms","venue":null,"work_id":"1849b757-5950-4646-ae52-7424d74f552c","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f35b57aada82bb02a6d0eed95b8cf9397c96e3090305a12dcfc0fc9bdfc3ef09","observation_id":"b67d31cf-318e-4478-b0c5-90dc941e0bda","resolution":{"observed_at":"2026-05-19T16:47:40.205725Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.10481","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ultrallada: Scaling the context length to 128k for diffusion large language models","venue":null,"work_id":"f893c5fb-e7de-4c8f-983a-baf01eeb95be","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:4fcfd4e6b1495b7e55df795d743e7c8466930bc0f602460c040881ff2ddbd61e","observation_id":"118dccbf-8fdd-450a-bed5-04a8b90ce193","resolution":{"observed_at":"2026-05-19T16:47:40.169261Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03874","last_updated":"2021-11-08T21:30:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-03-05T18:59:39Z","title":"Measuring Mathematical Problem Solving With the MATH Dataset","version":2},"cited_work":{"arxiv_id":"2103.03874","doi":"10.48550/arxiv.2103.03874","metadata_source":"pith","pith_arxiv_id":"2103.03874","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Measuring Mathematical Problem Solving With the MATH Dataset","venue":"cs.LG","work_id":"50652ac6-fb7c-4675-a2c2-159c241feb17","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2103.03874","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:308ae4f9b38b71cae32c5b2fb7308819a3fcc61b5ff0c6369537ed294afef816","observation_id":"d7e329c1-f37d-4c32-8e87-01adc69d4423","resolution":{"observed_at":"2026-05-19T16:47:40.160583Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-14T18:20:22.649941+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T18:20:22.649941+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.17206","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T21:18:59.430034Z","title":"Soft-masked diffusion language models","venue":null,"work_id":"fa9aa9b0-1d3a-4615-b566-60358b282a75","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:aa9d91f4d45e6547fd82338f43540ea6cbfab3c2a9058db4deec51cdb1c3bbb9","observation_id":"4b879057-4483-4ba4-b91f-579d8e183118","resolution":{"observed_at":"2026-05-19T16:47:40.117449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T14:37:16.225324Z","title":"Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851","venue":null,"work_id":"82ba805b-3e59-43c6-b37f-3aa1940eea68","year":2020},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:1d055077f9efba949aa10540d938c287c690bdf314c6bc99a850b5584c9dab3d","observation_id":"a6b395a0-fd2d-44de-a29d-bd39676f9482","resolution":{"observed_at":"2026-05-19T16:47:40.649571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2507.18578","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T22:57:26.546521Z","title":"Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs","venue":null,"work_id":"f5bcb45d-ff33-4079-a5c6-7af7dd36ff80","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:a5e5745b1c10273733ef0e9fdd30356ef8cb38952ab21fceb08a8eb860280f26","observation_id":"7b1b2f9d-f7fe-440e-b0a4-e3c9f14396e3","resolution":{"observed_at":"2026-05-19T16:47:40.155489Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2603.13319","last_updated":"2026-07-31T03:04:43Z","snapshot_observed_at":"2026-08-05T07:10:45.957024Z","submitted_at":"2026-03-04T11:43:19Z","title":"LightningRL: Breaking the Accuracy-Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2603.13319","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2603.13319","snapshot_observed_at":"2026-08-03T02:15:22.563508Z","title":"Lightningrl: Breaking the accuracy- parallelism trade-off of block-wise dllms via reinforcement learning","venue":null,"work_id":"31f5a8f4-86dc-42cd-8713-e1ab10e11898","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2603.13319","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:0e4836475715d06a8874ec986f2f5f2cbf42cf1a1f4f51f6e586b1ca7fa2b9e8","observation_id":"54612009-22a3-4466-b8e2-a04bc12cfa8a","resolution":{"observed_at":"2026-08-03T02:15:22.563508Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.22954","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T22:05:05.844217Z","title":"Residual Context Diffusion Language Models","venue":null,"work_id":"b45ad4c7-eec8-4c4d-a785-b6d4bd5c9b1a","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:1194ee1d534a818c0bc9d498fa74075ccaf76f33b3d226e2240d870a8498d0a2","observation_id":"05b085a7-3073-4240-90fb-4831088205a8","resolution":{"observed_at":"2026-05-19T16:47:40.174673Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2505.21467","doi":"10.48550/arxiv.2505.21467","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"S., Seo, J.-s., Zhang, Z., and Gupta, U","venue":"arXiv (Cornell University)","work_id":"2fbfcd17-7a6b-4979-912b-deca632607b1","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:ad4943fe86357303f73c6d091564dd93a0d2b20dcebfedff12c99bdf876f4d25","observation_id":"d557d995-19ef-43cb-a7e6-a30e57974f1b","resolution":{"observed_at":"2026-05-19T16:47:40.241824Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.09309","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mask tokens as prophet: Fine-grained cache eviction for efficient dllm inference","venue":null,"work_id":"b5993a71-088a-43ac-b506-fb203cd1b8c2","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:a016b526ab2380d621e9b942341065562ea978b9a412e94fb8491a4026e9e501","observation_id":"dccfa270-913e-450f-a41b-f7b9064f666a","resolution":{"observed_at":"2026-05-19T16:47:40.200430Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.00413","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T03:07:50.968632Z","title":"Accelerating diffusion llms via adaptive parallel decoding","venue":null,"work_id":"4ade588c-b9fd-4cde-8d73-9d8863d29913","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:3ab5d0cdddf820e3ddaf06196850ed5c94cee2e9e382553cfe407a4a939b5f34","observation_id":"98319453-8b35-48a7-aa4f-67c314efd1e6","resolution":{"observed_at":"2026-05-19T16:47:40.253339Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.19269","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T06:09:37.905425Z","title":"Cdlm: Consistency diffusion language models for faster sampling","venue":null,"work_id":"8079af86-c19d-490a-97d8-dabdc028ba25","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:cb586f44b64a8ff827b03a819c0497ddbcec1a08a3df9f413632f4d53d37aaee","observation_id":"d845d1f1-1fba-4911-925d-5d7104b3130c","resolution":{"observed_at":"2026-05-19T16:47:40.073297Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T12:53:51.199808Z","title":"Fast inference from transformers via speculative decoding","venue":null,"work_id":"1fbe276e-0625-47a5-88b5-ded8d9608969","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:286ed198358a1b80bfe7f243dec8b25811ef0a64b85b44eb73048da2ca4c66bc","observation_id":"ceb5d356-64ea-4779-9d34-064e44def973","resolution":{"observed_at":"2026-05-19T16:47:40.643389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions.Hugging Face repository, 13(9):9","venue":null,"work_id":"9cb7bd9c-5bb4-4e68-8c54-d202ee1cb827","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c52b9e8f2315fe5c7927d4875ab606f52c676bd24ea814c50a977d6a63e5ce98","observation_id":"d038e4c8-ef72-43e2-a4cd-e8534df55e8f","resolution":{"observed_at":"2026-05-19T16:47:40.635657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Beyond fixed: Variable-length denoising for diffusion large language models.arXiv e-prints, pages arXiv–2508","venue":null,"work_id":"39d221d3-b191-4e90-a735-283d4155b688","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:d3d6741f4251e481865afd22a0ea89ffba01bf0f47f05d39a6366d8694b1409d","observation_id":"48799835-6853-44a1-a40a-f53c3413c362","resolution":{"observed_at":"2026-05-19T16:47:40.637647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10875","last_updated":"2026-06-04T15:16:30Z","snapshot_observed_at":"2026-07-06T22:13:04.624677Z","submitted_at":"2025-08-14T17:47:22Z","title":"A Survey on Diffusion Language Models","version":3},"cited_work":{"arxiv_id":"2508.10875","doi":"10.48550/arxiv.2508.10875","metadata_source":"pith","pith_arxiv_id":"2508.10875","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Lavida: A large diffusion model for vision-language understanding.Advances in neural information process- ing systems, 2025b","venue":"cs.CL","work_id":"e44cc99a-c47c-4c26-9848-e709df566178","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.10875","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:7c46710e8fa3e6ce46f7d29c1171c33eae45c115b5f960526735cd07297f7aeb","observation_id":"c85486b1-4c6a-4c00-a02e-8fa6bf6db2a7","resolution":{"observed_at":"2026-06-05T02:16:19.040077Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15077","last_updated":"2025-03-04T13:58:39Z","snapshot_observed_at":"2026-08-03T09:40:31.365295Z","submitted_at":"2024-01-26T18:59:01Z","title":"EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty","version":3},"cited_work":{"arxiv_id":"2401.15077","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.15077","snapshot_observed_at":"2026-07-10T21:57:38.979373Z","title":"EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty","venue":"cs.LG","work_id":"9d4637dd-1cab-4f10-82d4-8c8d14bb96ed","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2401.15077","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:0531fbfb3710e9ff77b33b4a37bcaa845d632aa39086c2137c8aa53d389af94c","observation_id":"fcb72500-a34f-4078-8249-9978c5e50fb0","resolution":{"observed_at":"2026-05-19T16:47:40.016164Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-06T16:32:39.114869Z","title":"Let’s verify step by step","venue":null,"work_id":"7c9f7d5c-e081-4728-8d71-07bae6642366","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:e6b3f27731759492a726adcf45c50ab425a1a1f4362fef551398b1a6a0f89d69","observation_id":"bf138594-10fa-4c18-b374-839aab18c29e","resolution":{"observed_at":"2026-05-19T16:47:40.639396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.22737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T21:18:59.427303Z","title":"Wedlm: Reconciling diffusion language models with standard causal atten- tion for fast inference.arXiv preprint arXiv:2512.22737","venue":null,"work_id":"d5210ea8-e37e-4dcd-b04e-5f1f8909ede0","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:2bcae15989bd7b633df4ffa5718f979a390ee8c5b26cd89d73344f37b71b1603","observation_id":"ac47653f-8649-46b0-81a1-cd60a7b795b3","resolution":{"observed_at":"2026-05-19T16:47:40.010943Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.08923","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T03:07:52.191436Z","title":"Tidar: Think in diffusion, talk in autoregression","venue":null,"work_id":"ee07aeca-ea93-4394-85e4-7bbe1b5565d0","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:1d064ce1fe633ea6504647e58a8abecdd3de7270380b48d6d9ab3203a22652cc","observation_id":"fe652e8e-63fb-473c-8d2a-625f5071a8f9","resolution":{"observed_at":"2026-05-19T16:47:40.186302Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Longllada: Unlocking long context capabilities in diffusion llms","venue":null,"work_id":"6d4821c3-b0b9-4cd1-84b4-5243fc0bd98f","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:8f3007b05b2f406bfd3a01276428fb8680cb8039abcfecc208f954991228abb4","observation_id":"fe69e76a-9a67-4813-9d2a-941ac8a4f2c5","resolution":{"observed_at":"2026-05-19T16:47:40.625382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2603.25406","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T10:59:46.973911Z","title":"Mmada-vla: Large diffusion vision-language-action model with unified multi-modal instruction and generation","venue":null,"work_id":"739b572f-e3f9-45a6-8393-947de34fb2ff","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:b21e01cf24e9be67fd5ea836cde9f8c8611c96a327f4e9cb719a46ee26162059","observation_id":"321c5f8d-b6b1-49b0-ab16-0eca19b879d9","resolution":{"observed_at":"2026-05-19T16:47:40.098053Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06295","last_updated":"2026-06-06T06:01:00Z","snapshot_observed_at":"2026-08-03T04:37:06.799759Z","submitted_at":"2025-05-17T15:50:46Z","title":"dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching","version":3},"cited_work":{"arxiv_id":"2506.06295","doi":"10.48550/arxiv.2506.06295","metadata_source":"pith","pith_arxiv_id":"2506.06295","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Liu, J., Dong, X., Ye, Z., Mehta, R., Fu, Y ., Singh, V ., Kautz, J., Zhang, C., and Molchanov, P","venue":"cs.LG","work_id":"fd1cde49-2043-4004-96e2-a9cca486ec0a","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2506.06295","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:1a32bc336010c52bf846ab3478cd406483ba58197e113f1b90ef5576b42d750c","observation_id":"21a3f967-5630-4941-9526-69130a4a6542","resolution":{"observed_at":"2026-06-03T13:05:37.261622Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.02159","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T04:57:38.682198Z","title":"Focus- dllm: Accelerating long-context diffusion llm inference via confidence-guided context focusing","venue":null,"work_id":"ea266d9f-5e94-48e7-bc9b-707d46b48aea","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:7c85cad13ef01c399b95acab10a3d12cdfd48dcdf6b33d50dad5e3216d9efae8","observation_id":"0704e33f-2eb4-4526-96c1-bc78b0f29fa7","resolution":{"observed_at":"2026-05-19T16:47:40.057510Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Discrete diffusion language modeling by estimating the ratios of the data distribution","venue":null,"work_id":"78feca41-ef6c-4bc8-9d7e-a1c31d5b2a74","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f825dd591c9ad26cddace604602469ae4ebccdd0352b3436a115da61f79a444e","observation_id":"cb5db8cf-fa6e-4085-80b1-fd13af6a92e9","resolution":{"observed_at":"2026-05-19T16:47:40.629224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.13599","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T17:38:43.590996Z","title":"Diffusion in diffusion: Breaking the autoregressive bottleneck in block diffusion models","venue":null,"work_id":"bacaca6e-6353-42e5-beab-e7abac45a3e3","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:912a5737026d77a0646f4a672ab493dcc7a203cb4e13cffc19a0edee25983316","observation_id":"49602da2-16fa-4602-9943-7201afc7db48","resolution":{"observed_at":"2026-05-19T16:47:40.045984Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15781","last_updated":"2025-05-21T17:32:10Z","snapshot_observed_at":"2026-08-01T20:24:14.008213Z","submitted_at":"2025-05-21T17:32:10Z","title":"dKV-Cache: The Cache for Diffusion Language Models","version":1},"cited_work":{"arxiv_id":"2505.15781","doi":"10.48550/arxiv.2505.15781","metadata_source":"pith","pith_arxiv_id":"2505.15781","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"dkv-cache: The cache for diffusion language models","venue":"cs.CL","work_id":"8bba2afd-bafd-4ccb-af6d-58855e9f3967","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.15781","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f712593d42a98270c6ba438b5b7baf0cd8fb2aac7c443e1c7432eb8eaaeff66a","observation_id":"5d555c91-64eb-4ac2-bef7-a9d3b48b7942","resolution":{"observed_at":"2026-05-19T16:47:40.235722Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.08666","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T22:52:44.928734Z","title":"dinfer: An efficient inference framework for diffusion language models","venue":null,"work_id":"620d2165-4a9e-40a3-af33-3c1f4803609b","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:cdc921174fe340c8b7082afea950f9b390f045f412cc9d974ee00dbb0abc151d","observation_id":"34e5b913-7203-4903-bd50-4de9a0199e8d","resolution":{"observed_at":"2026-05-19T16:47:40.048771Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A diverse corpus for evaluating and developing english math word problem solvers","venue":null,"work_id":"618bcb86-4f3a-467f-aab6-bdd1d027c460","year":2021},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:2755f93dce6c0d0a6c0c9f04ae8f2d204627a715708cda02b3eadcdac77fa1c3","observation_id":"3d92801c-2c43-4c43-9dee-635986241f23","resolution":{"observed_at":"2026-05-19T16:47:40.623449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.03276","doi":"10.48550/arxiv.2511.03276","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Diffusion language models are super data learners","venue":"ArXiv.org","work_id":"f40e0def-a5c2-45ca-a0a9-742986113aa6","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:a44cbb6759c3b8cdce96299c546a7510454ebb32bc7b6e8e5d667c75fa6342b5","observation_id":"523662f7-b1f4-4877-952a-13c385569025","resolution":{"observed_at":"2026-05-19T16:47:40.040125Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.15165","last_updated":"2026-06-08T15:43:52Z","snapshot_observed_at":"2026-08-03T11:44:38.056149Z","submitted_at":"2026-01-21T16:41:58Z","title":"The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models","version":4},"cited_work":{"arxiv_id":"2601.15165","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.15165","snapshot_observed_at":"2026-07-03T09:17:48.826210Z","title":"The flexibility trap: Why arbitrary order limits reasoning potential in diffusion language models","venue":"cs.CL","work_id":"c3023e0a-7cf0-43eb-8916-685a4bbb7426","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2601.15165","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:17749b44bf210932139c7a23c72c87b0d240b27fdbfd6ec1c991b626f42cd1da","observation_id":"85c2ee36-6128-4b95-b02c-72bceeee88b5","resolution":{"observed_at":"2026-06-09T03:08:03.844139Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.09992","last_updated":"2025-10-18T15:35:05Z","snapshot_observed_at":"2026-08-04T04:34:22.998376Z","submitted_at":"2025-02-14T08:23:51Z","title":"Large Language Diffusion Models","version":3},"cited_work":{"arxiv_id":"2502.09992","doi":"10.48550/arxiv.2502.09992","metadata_source":"pith","pith_arxiv_id":"2502.09992","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Large Language Diffusion Models","venue":"cs.CL","work_id":"cce0f4b3-ed4d-4375-b84d-3f01316016c1","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2502.09992","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:26c4f662accdd5344d2aca4c792ceb50b28d3bdd7c4f9b52c38a849a8836609e","observation_id":"01c159fd-fa74-493a-bd94-1ae458850163","resolution":{"observed_at":"2026-05-19T16:47:40.037143Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.09675","last_updated":"2026-05-13T05:10:13Z","snapshot_observed_at":"2026-08-03T21:26:50.606588Z","submitted_at":"2025-12-10T14:20:07Z","title":"d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models","version":3},"cited_work":{"arxiv_id":"2512.09675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.09675","snapshot_observed_at":"2026-07-03T20:28:55.626839Z","title":"d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models","venue":"cs.CL","work_id":"f758ad04-0d63-48c2-ba04-6b73c214954c","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2512.09675","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:b32c5be7618547576535b35830047e218eb8e68de9dd8a8b7c2e378a76db379d","observation_id":"bfc8249b-bc4a-49a6-aa80-f4bb29ca5a92","resolution":{"observed_at":"2026-05-19T16:47:40.042885Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01952","last_updated":"2023-07-04T23:04:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-04T23:04:57Z","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","version":1},"cited_work":{"arxiv_id":"2307.01952","doi":"10.48500/arxiv.2307.01952","metadata_source":"pith","pith_arxiv_id":"2307.01952","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","venue":"cs.CV","work_id":"8034c587-fba6-4941-87ba-c98f2ac962cb","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:0f885101c6c3ef9e9ca73158d284a153615b2d3a8edb89ece391f559ebf6e655","observation_id":"1b0a5bb4-1a3d-4175-8cf8-b600f99acff9","resolution":{"observed_at":"2026-05-19T16:47:40.051638Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hierarchy decoding: A training-free parallel decoding strategy for diffusion large language models","venue":null,"work_id":"ac870a98-6593-4e7b-8427-b1fa93bc3b6f","year":null},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:63f77b51f673703e82dbbe994c44b1cd9d8fc02ec3619ad75b1fd9492ea0c47f","observation_id":"c63cb812-4bfc-45cc-b69f-39cc928b0502","resolution":{"observed_at":"2026-05-19T16:47:40.627284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.07568","doi":"10.48550/arxiv.2601.07568","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"d3llm: Ultra-fast diffusion llm using pseudo- trajectory distillation.arXiv preprint arXiv:2601.07568","venue":"Open MIND","work_id":"c66cf43f-ca47-4958-9037-5212d2e00f9d","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:8ae45c6fe2a60a129b2e1e3458db9a272db6c50e306bc70e9f9191695ca5ee93","observation_id":"4c26be6a-c22a-4d2f-a2f7-5cb1d719764f","resolution":{"observed_at":"2026-05-19T16:47:40.183410Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.08554","doi":"10.48550/arxiv.2510.08554","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Improving reasoning for diffusion language models via group diffusion policy optimization","venue":"arXiv (Cornell University)","work_id":"92530ab8-ecd9-4f9c-9a0e-4a3564931b48","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c95928f71d69d0d8368a0600cc7f47d2e7ea40a4f1e8b5afc06f9b52a8b980fb","observation_id":"4db0fdcd-815a-4d84-9ee9-e6d739bd7420","resolution":{"observed_at":"2026-05-19T16:47:40.013623Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T18:05:18.649491Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"3cba96fb-e636-4639-8d43-2f25ce21d4d1","year":2022},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:15b8cd4fce09b3c22b84792493d9d78f514a59e1dc62206b552993a27a373e0b","observation_id":"5113c4cb-ca3c-4eac-927e-dd9c1c13f5a8","resolution":{"observed_at":"2026-05-19T16:47:40.619456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation","venue":null,"work_id":"e9c23fc5-1eb4-4333-8dc1-e8da6c4f5dfc","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:117c457b5aa727f8a21dd255b8e12a7d8da6d9f546ae59da907e9926c63e5522","observation_id":"b651b713-0d95-4e6b-b731-a4f65b450015","resolution":{"observed_at":"2026-05-19T16:47:40.621499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T08:26:05.768951Z","title":"Simple and effective masked diffusion language models.Advances in Neural Information Processing Systems, 37:130136–130184","venue":null,"work_id":"5c1394cd-e030-4840-800a-032cca7d3396","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f3f844bb50f09ba52b65421a4fb6767f755ea0fa4366339a2a8d1437ec6841db","observation_id":"941a5800-589e-4913-9f56-eab1aedbd4da","resolution":{"observed_at":"2026-05-19T16:47:40.617446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.10892","doi":"10.48550/arxiv.2506.10892","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The diffusion duality","venue":"ArXiv.org","work_id":"4d71092a-cda4-4bad-b660-5932ea447f30","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:2864bd64902226c6f841d422fcf64a39fa1cc943da057c7aa8338a9aed51d46b","observation_id":"72dfa17c-bda8-4f8b-b9c2-6613f20f5e85","resolution":{"observed_at":"2026-05-19T16:47:40.256202Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Simple guidance mecha- nisms for discrete diffusion models","venue":null,"work_id":"284260d3-edc7-4c78-96b7-fdc610029e4d","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:9c1ef4cf0000e2918e913a763233a339279de2aaa59a5abd7dd9aa0b40d4d16c","observation_id":"9dd78df9-7187-49eb-86eb-fbb7e37fe6aa","resolution":{"observed_at":"2026-05-19T16:47:40.612669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scaling beyond masked diffusion language models.arXiv e-prints, pages arXiv–2602","venue":null,"work_id":"0420c7b4-9f61-44bb-9eb1-c86b4898bacf","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:916eaecd4aa8881ca960bc3151b50ae2d667d261c64fc7fbac2f20b1d1cf4655","observation_id":"1bfd359d-921d-454c-901b-d02c692cda06","resolution":{"observed_at":"2026-05-19T16:47:40.608421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Simplified and generalized masked diffusion for discrete data.Advances in neural information processing systems, 37:103131– 103167","venue":null,"work_id":"1cd4c19a-6a78-4ebc-b41f-6ed20cdb8534","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:7d0bc99c03e641f58b454c5290357db111ba0bc4260585c3ff6fffb41fc5e22a","observation_id":"ff5cd38b-da53-4139-a7f6-49389811e7f4","resolution":{"observed_at":"2026-05-19T16:47:40.610577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":"2010.02502","doi":"10.48550/arxiv.2010.02502","metadata_source":"pith","pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Denoising Diffusion Implicit Models","venue":"cs.LG","work_id":"8fa2128b-d18c-405c-ac92-0e669cf89ac0","year":2020},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:6645342853fc1b5279d55c041c66179082b9698057ff6d8aa72f39e18505e701","observation_id":"4f25fd4c-6bb2-4506-91ce-2e0ae0fad22d","resolution":{"observed_at":"2026-05-19T16:47:40.005196Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-12T13:49:41.147667+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T13:49:41.147667+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sparse-dllm: Accelerating diffusion llms with dynamic cache eviction","venue":null,"work_id":"6cc3f093-5af1-48e0-a08e-db2fd9b00003","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:3bd3b0f3abf472398930316a00f08070f0f951db81b4b508d8876374a42d571a","observation_id":"ae4830bc-c50a-4873-94a4-29f17107a21c","resolution":{"observed_at":"2026-05-19T16:47:40.615401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.02193","last_updated":"2025-08-04T08:43:01Z","snapshot_observed_at":"2026-07-06T22:07:21.387432Z","submitted_at":"2025-08-04T08:43:01Z","title":"Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference","version":1},"cited_work":{"arxiv_id":"2508.02193","doi":"10.48550/arxiv.2508.02193","metadata_source":"pith","pith_arxiv_id":"2508.02193","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference","venue":"cs.CL","work_id":"7412f5f3-8e71-41c1-9c69-d4ca250b18fa","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.02193","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:07f94619367d2087db5dcf5cf0fbb4df1b54ec828d70e128a33b2ce5a8eb620a","observation_id":"ec6392f3-d372-44b7-9ca7-6e311383e560","resolution":{"observed_at":"2026-05-19T16:47:40.018746Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2507.08838","doi":"10.48550/arxiv.2507.08838","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"wd1: Weighted policy optimization for reasoning in diffusion language models.arXiv preprint arXiv:2507.08838","venue":"ArXiv.org","work_id":"127e8eef-f734-4f65-bb7d-83a8835bc6f4","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:2802d1da210d3689bb41529cb8fdbb0e6dfb93e075c645b6adb59f9134ed4497","observation_id":"72e74ac9-2d62-4138-af40-29ed66241b3a","resolution":{"observed_at":"2026-05-19T16:47:40.067108Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.06776","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T13:26:58.852697Z","title":"From next-token to next-block: A principled adaptation path for diffusion llms.arXiv preprint arXiv:2512.06776","venue":null,"work_id":"cc2f24b0-fbc8-429b-8d36-e789d7f8fbfc","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:fcb2d4cd041e5b8371068a86899c4b24de400b5ceada74f34e443089d35315b2","observation_id":"7ef35537-3884-40e8-816c-c248b5a744c9","resolution":{"observed_at":"2026-05-19T16:47:40.211630Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.04482","last_updated":"2025-06-09T14:23:45Z","snapshot_observed_at":"2026-07-06T20:47:51.382034Z","submitted_at":"2025-03-06T14:30:55Z","title":"Generalized Interpolating Discrete Diffusion","version":2},"cited_work":{"arxiv_id":"2503.04482","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.04482","snapshot_observed_at":"2026-07-03T09:17:48.810706Z","title":"Generalized interpolating discrete diffusion","venue":null,"work_id":"2dacff6a-6956-44e8-924d-396b276b2618","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2503.04482","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:3a84290342b641f7ddddff58d77fff1144a2ab9f29c192bbb6260b0ef6e23603","observation_id":"29ce9cab-d683-470b-b703-6dd57fed0bbc","resolution":{"observed_at":"2026-05-19T16:47:40.262286Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2510.06133","last_updated":"2026-05-26T03:39:22Z","snapshot_observed_at":"2026-08-04T11:16:44.535486Z","submitted_at":"2025-10-07T17:08:33Z","title":"CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit","version":3},"cited_work":{"arxiv_id":"2510.06133","doi":null,"metadata_source":"pith","pith_arxiv_id":"2510.06133","snapshot_observed_at":"2026-06-28T22:52:44.905502Z","title":"CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit","venue":"cs.CL","work_id":"e4e71114-241e-4f6b-bb2c-4f3229a14b0f","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2510.06133","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:fbdaf8f1063337fb3c4e4840a8ba2e3023fbf7aa4c390c8ad87d3916347abbf3","observation_id":"4ef1f809-d9ff-429b-ae8a-820cb2ca4c14","resolution":{"observed_at":"2026-05-19T16:47:40.238631Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.09192","last_updated":"2025-08-08T04:51:37Z","snapshot_observed_at":"2026-07-06T22:11:57.493922Z","submitted_at":"2025-08-08T04:51:37Z","title":"Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing","version":1},"cited_work":{"arxiv_id":"2508.09192","doi":null,"metadata_source":"pith","pith_arxiv_id":"2508.09192","snapshot_observed_at":"2026-07-11T03:07:51.302542Z","title":"Diffusion llms can do faster-than-ar inference via dis- crete diffusion forcing.arXiv preprint arXiv:2508.09192","venue":"cs.LG","work_id":"3fd87c40-91ee-403b-9781-58b4e2feb625","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.09192","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:53db27830273593f747c348e32adeaf207af2bf916b225bc14bece5fa714d269","observation_id":"0970f9db-cd53-430c-b996-d3d44ee124ee","resolution":{"observed_at":"2026-05-19T16:47:40.244732Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sparsed: Sparse attention for diffusion language models","venue":null,"work_id":"a1d1ebb1-6cce-45eb-ae20-72e3ca1a40c3","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:1c49db8fefb5825196815fbb6d3d6ed16e90c6ff7b17c36aacb69452abfcdb89","observation_id":"c1a6f6da-3789-4914-8661-e55770e4095a","resolution":{"observed_at":"2026-05-19T16:47:40.655437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T11:37:03.941805Z","title":"Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837","venue":null,"work_id":"3256b5a6-76d9-460c-ad77-5d232058ad6d","year":2022},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:9717e370d26fdf2c1a2d84b291df63895892fb7b835f64b99143398c066d97d4","observation_id":"5956d383-46df-4391-b460-8c458333a14e","resolution":{"observed_at":"2026-05-19T16:47:40.651783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.10848","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T03:07:51.733423Z","title":"Accelerating diffusion large language models with slowfast sampling: The three golden principles","venue":null,"work_id":"121d5d8f-5ee6-4a5d-8ae0-c4070efcebc8","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:0e73662bac8985a3186cbb4b830282464f20e4775173ab474f4cd3d5d3b9b379","observation_id":"dac7a471-0737-476c-b919-ac02c3912b73","resolution":{"observed_at":"2026-05-19T16:47:40.208536Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.06932","last_updated":"2025-09-10T14:34:25Z","snapshot_observed_at":"2026-08-04T22:55:29.306356Z","submitted_at":"2025-09-08T17:45:40Z","title":"LLaDA-VLA: Vision Language Diffusion Action Models","version":2},"cited_work":{"arxiv_id":"2509.06932","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.06932","snapshot_observed_at":"2026-07-02T18:57:16.674514Z","title":"Llada-vla: Vision language dif- fusion action models","venue":null,"work_id":"a0a2d268-560d-4085-a4e7-ddd82d9cd062","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2509.06932","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:461b7787f65cb7239703c5973916e54df34de6e123bcb854158406bc3f1e706f","observation_id":"6c60f7ac-ceee-4c7e-a488-72c09becbfa4","resolution":{"observed_at":"2026-05-19T16:47:40.177584Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.26328","doi":"10.48550/arxiv.2509.26328","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fast- dllm v2: Efficient block-diffusion llm.arXiv preprint arXiv:2509.26328","venue":"arXiv (Cornell University)","work_id":"248fd492-8bf7-4ce9-a1df-130b5b976e36","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:db6c1d11594cb8de1905e9b696e948d044b797b57202c1fe875422e13eb4e10e","observation_id":"c101f9b6-ac6e-4c84-afaf-1d796822d8ef","resolution":{"observed_at":"2026-05-19T16:47:40.203090Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.22618","last_updated":"2025-07-03T04:51:05Z","snapshot_observed_at":"2026-07-06T21:32:23.537939Z","submitted_at":"2025-05-28T17:39:15Z","title":"Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding","version":3},"cited_work":{"arxiv_id":"2505.22618","doi":"10.48550/arxiv.2505.22618","metadata_source":"pith","pith_arxiv_id":"2505.22618","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding","venue":"cs.CL","work_id":"9f6c2a70-9830-48ae-b181-6b5b1cbfae97","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.22618","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:9ed08bca49da28f9bc573c97cce5af2359d1743c68c9b4c8090dc771f98b0c7d","observation_id":"312f8653-2ee4-43e9-a47c-f805db3c95d4","resolution":{"observed_at":"2026-05-19T16:47:40.132755Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-25T17:53:19.96554+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T17:53:19.96554+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Streaming-dllm: Accelerating diffusion llms via suffix pruning and dynamic decoding.arXiv e-prints, pages arXiv–2601","venue":null,"work_id":"8843d138-fc41-47f1-bc3c-e5d8875d3d93","year":2026},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f306fd011f74c2308ac7938885f5a8fd3cf01c1945990aa3605c95317cf29029","observation_id":"9e66a6d9-0138-45d8-9259-aee29688fe90","resolution":{"observed_at":"2026-05-19T16:47:40.641358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2510.01544","last_updated":"2026-04-11T19:22:11Z","snapshot_observed_at":"2026-07-06T22:31:30.171287Z","submitted_at":"2025-10-02T00:34:15Z","title":"Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards","version":2},"cited_work":{"arxiv_id":"2510.01544","doi":null,"metadata_source":"pith","pith_arxiv_id":"2510.01544","snapshot_observed_at":"2026-07-03T20:28:55.643155Z","title":"Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards","venue":"cs.AI","work_id":"d49901f0-21e7-4fab-b72a-f20a9fc976cb","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2510.01544","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:86b000373c80d3f5d8e2942c305fa8bbe5ee9accd2b0abb5993d880d9e50eb06","observation_id":"340f6eb7-c523-43a4-a80a-871506bae0c3","resolution":{"observed_at":"2026-05-19T16:47:40.171892Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01142","last_updated":"2025-09-01T05:30:56Z","snapshot_observed_at":"2026-08-04T22:18:34.059622Z","submitted_at":"2025-09-01T05:30:56Z","title":"Dream-Coder 7B: An Open Diffusion Language Model for Code","version":1},"cited_work":{"arxiv_id":"2509.01142","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.01142","snapshot_observed_at":"2026-07-11T03:07:52.385541Z","title":"Dream-coder 7b: An open diffusion language model for code.arXiv preprint arXiv:2509.01142","venue":"cs.CL","work_id":"8a7c9708-6012-4156-8cca-f10969908d10","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2509.01142","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:ed8fbba5befba8ec9ed8fc077708a47a02eb43a59ad38773067ae04524cf5ed7","observation_id":"44df5d78-1b54-481e-bb70-72615d29e6b4","resolution":{"observed_at":"2026-05-19T16:47:40.149741Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.14090","last_updated":"2025-08-26T02:18:25Z","snapshot_observed_at":"2026-07-06T22:15:12.721846Z","submitted_at":"2025-08-14T09:30:17Z","title":"DLLMQuant: Quantizing Diffusion-based Large Language Models","version":2},"cited_work":{"arxiv_id":"2508.14090","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.14090","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dllmquant: Quantizing diffusion-based large language models","venue":null,"work_id":"f5af1991-ebb5-4d8d-9ea7-d54bcf4b5ad1","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.14090","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c7b9a15966137e3b18709b89ad7679fd95a81f0369c6f625920cb3598fc3a6a3","observation_id":"f34db659-a660-45ea-8f7b-fc21c27674e7","resolution":{"observed_at":"2026-05-19T16:47:40.120619Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.16229","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T09:25:40.607817Z","title":"Lopa: Scaling dllm inference via looka- head parallel decoding.arXiv preprint arXiv:2512.16229","venue":null,"work_id":"fdca2545-30a0-40eb-ad09-a0a5d6573203","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:fbcb63b6b46408aca3556b3288ebb0ea52a10f7fac0f5f5d458b1232e31c8f7b","observation_id":"4af869ee-6916-4fc6-aad7-2eff5628c57c","resolution":{"observed_at":"2026-05-19T16:47:40.070118Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15809","last_updated":"2025-09-25T02:40:45Z","snapshot_observed_at":"2026-08-05T05:27:10.277230Z","submitted_at":"2025-05-21T17:59:05Z","title":"MMaDA: Multimodal Large Diffusion Language Models","version":2},"cited_work":{"arxiv_id":"2505.15809","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.15809","snapshot_observed_at":"2026-07-11T03:07:51.413936Z","title":"MMaDA: Multimodal Large Diffusion Language Models","venue":"cs.CV","work_id":"9d626cf3-094e-4960-9e71-a00a47158639","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.15809","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:e5aba9039e56844776b2e8441c480b2faf9ca8f9cbbee1ed3d3758c6112f228e","observation_id":"ecbb25a0-6515-4899-ae16-743bcb6f6f51","resolution":{"observed_at":"2026-05-19T16:47:40.258886Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.22615","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T19:08:50.463698Z","title":"Dream-vl & dream-vla: Open vision-language and vision-language-action models with diffusion language model backbone","venue":null,"work_id":"eae31ae1-2642-4b4c-8618-74c0755fd3ae","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:ca10d2ec3018d7a49cb3146bda1910971847a905368735d9d45b850863e787f2","observation_id":"f0427e98-cf85-4aaf-b175-39a6d27d54e9","resolution":{"observed_at":"2026-05-19T16:47:40.130003Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.15487","last_updated":"2025-08-21T12:09:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-21T12:09:58Z","title":"Dream 7B: Diffusion Large Language Models","version":1},"cited_work":{"arxiv_id":"2508.15487","doi":"10.48550/arxiv.2508.15487","metadata_source":"pith","pith_arxiv_id":"2508.15487","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Dream 7B: Diffusion Large Language Models","venue":"cs.CL","work_id":"a8a49dbd-ad10-4c79-b1aa-3ad5173887ad","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2508.15487","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:01efb8ac7b201b478ffe6bcd305ef2af50ffb5d7e451a50aa248288fba09d826","observation_id":"eee2e101-4c06-45fa-8d97-f79facde1dcc","resolution":{"observed_at":"2026-05-19T16:47:40.127061Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffusion models in text generation: a survey.PeerJ Computer Science, 10:e1905","venue":null,"work_id":"1e2435db-dac1-4ad2-a981-c0d39f3ae97d","year":2024},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:c167d1587d63bce79e77ff284d853338dffcf638fdb2d431da994a0c85f2899d","observation_id":"e03ca79e-bfb9-4590-aace-1b5b9ca9ccac","resolution":{"observed_at":"2026-05-19T16:47:40.631142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16933","last_updated":"2025-06-04T05:52:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-22T17:23:26Z","title":"LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning","version":2},"cited_work":{"arxiv_id":"2505.16933","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.16933","snapshot_observed_at":"2026-07-11T03:07:52.266883Z","title":"LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning","venue":"cs.LG","work_id":"0cc20892-a1cb-4674-af31-8b884e2a3a79","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.16933","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:4f1fced807d143dbc48b45d3b6eb25c593574ced436f0d67ead08523f8db9079","observation_id":"48172090-4760-4a73-96a6-c70627854ba7","resolution":{"observed_at":"2026-05-19T16:47:40.114126Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.13759","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T17:35:51.719402Z","title":"Discrete diffusion in large language and multimodal models: A survey","venue":null,"work_id":"58bdb31e-9c01-4d67-bf4e-bae971b88a56","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:f388183761df9e6a19512ece7cff726e1aa1968aad75a6016bfe50e611c63319","observation_id":"43e8f6d8-cc14-4e0d-a36e-db703165fd4b","resolution":{"observed_at":"2026-05-19T16:47:40.250479Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16990","last_updated":"2025-05-26T02:04:39Z","snapshot_observed_at":"2026-08-04T14:44:24.484837Z","submitted_at":"2025-05-22T17:55:04Z","title":"Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding","version":2},"cited_work":{"arxiv_id":"2505.16990","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.16990","snapshot_observed_at":"2026-07-11T03:07:51.665307Z","title":"Dimple: Discrete diffusion multimodal large language model with parallel decoding.arXiv preprint arXiv:2505.16990","venue":"cs.CV","work_id":"6d9ab858-5467-437a-80dc-c4ee9dac2f26","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"cited_paper":"/paper/2505.16990","citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:94b1ec40e40d38de727d8d5aaf3f50449bc83051da7ed6c5514cd2f7f52e5230","observation_id":"956eb3e6-2eda-4cb2-a710-12a85889c4a2","resolution":{"observed_at":"2026-05-19T16:47:40.107983Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.15713","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffu- sionvl: Translating any autoregressive models into diffusion vision language models","venue":null,"work_id":"2198d3a7-f4a3-4664-8742-5bbf5320eb07","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:fee4f354f7149685825f2d126deccebb9ced1e85320b9669cff6168510651c62","observation_id":"7defe5d8-8107-422b-a85e-edcfe990b19e","resolution":{"observed_at":"2026-05-19T16:47:40.060659Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.08712","doi":"10.48550/arxiv.2508.08712","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A survey on parallel text generation: From parallel decoding to diffusion language models","venue":"ArXiv.org","work_id":"5ed8cd4c-2414-4824-bac0-afafbb7ca3ec","year":2022},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:45f04525c87ebdeeeb368416a0312365b1daa0f6431e5c47fe73333c504d0962","observation_id":"08f5c689-bd03-40dd-9c88-9b1d753f4d36","resolution":{"observed_at":"2026-05-19T16:47:40.104681Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T17:35:10.861683Z","title":"Adding conditional control to text-to-image diffusion models","venue":null,"work_id":"3168d701-c64b-4fb9-808f-b1e9e35b1bf5","year":2023},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:a6c0d2ee834e26a5fdb376cd94e686915b7531176b58f0df20acbd0d0f617301","observation_id":"95a4ab81-04a5-4b77-a1dd-ecf8a2403360","resolution":{"observed_at":"2026-05-19T16:47:40.633207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.15596","doi":"10.48550/arxiv.2512.15596","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Corrective diffusion language models","venue":"Open MIND","work_id":"0818c035-7b0f-4ad9-9464-166ad2da79fc","year":2025},"citing_paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs","version":3},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-05-19T16:46:56.743268Z"},"links":{"citing_paper":"/paper/2604.08302"},"observation_digest":"sha256:3d2dc74bd5287572f0505a75cd578a88c8dfca076657c47e4c4c3d5376a9416c","observation_id":"8abb7444-db64-4f6c-b9ed-9da0fa83d53b","resolution":{"observed_at":"2026-05-19T16:47:40.063620Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.08302","last_updated":"2026-05-15T04:19:14Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:35:42Z","title":"DMax: Aggressive Parallel Decoding for dLLMs"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":1,"verified_exact":74,"verified_fuzzy":23},"total_outbound_references":110},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 100 of 110 outbound references and 5 inbound Pith citation observations for arXiv:2604.08302."}