{"as_of":"2026-08-05T14:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:40fd619c63d929ebfe2845fc1f40525160a58ee3e1620a6815240c1b9d386fd7","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-09T14:59:49.792976Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2605.01373/citation-record","integrity":"/paper/2605.01373/integrity","json":"/paper/2605.01373/citation-record.json","paper":"/paper/2605.01373"},"outbound":[{"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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2108.07732","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:841991b75d40fe15f3d6e9d6476e12513a41599e778afea5f805eb5a6b4fd27f","observation_id":"ed9ea4cd-9479-423a-bb35-546dc24a3c06","resolution":{"observed_at":"2026-05-11T16:46:22.584769Z","resolver_source":"local_arxiv","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":{"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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2512.15745","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:0de142a798e20678c11da45e1f5e2441469aaf0c8f0140bddc3ac97d83cab2d1","observation_id":"6adb80a2-e705-4bf8-a236-74a4592f01e1","resolution":{"observed_at":"2026-05-14T18:53:21.210170Z","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":"2603.22248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T12:49:52.463594Z","title":"Confidence-based decoding is provably efficient for diffusion language models.arXiv preprint arXiv:2603.22248","venue":null,"work_id":"91212673-3b63-4444-a822-3c416156a06b","year":2026},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:0744e1da8f9e0190631029324857720d41a7690d8b23eec740fde0a6f78aaf21","observation_id":"8b8d516c-7317-4602-b440-e679206d61cb","resolution":{"observed_at":"2026-05-11T16:46:22.760557Z","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":"Search or accelerate: Confidence-switched position beam search for diffusion language models","venue":null,"work_id":"ee276fc8-4737-48aa-9e94-32773b239470","year":2026},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:13856203a2d23f89cac46ef360c3905a42febd710934bfe9ee07a9ac112a948c","observation_id":"81039830-4f5d-402a-b489-1d4c255c20a6","resolution":{"observed_at":"2026-05-26T01:36:29.250614Z","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":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":"2107.03374","doi":"10.48550/arxiv.2107.03374","metadata_source":"pith","pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Evaluating Large Language Models Trained on Code","venue":"cs.LG","work_id":"042493e9-b26f-4b4e-bbde-382072ca9b08","year":2021},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:f7c87adb2b75f689ccc09dbc691d6ff142966990d1cfb475a832ad46879f57c6","observation_id":"d1c69398-eda9-4004-af99-d454148ddda3","resolution":{"observed_at":"2026-05-11T16:46:21.419346Z","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":"2026-08-01T08:08:23.404839+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T08:08:23.404839+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":"2509.25604","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rfg: Test-time scaling for diffusion large language model reasoning with reward-free guidance.arXiv preprint arXiv:2509.25604","venue":null,"work_id":"1c67fe64-47a5-4854-a29f-d315a5cdcb35","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:f9727e8998f79fe3c7c1e7f790f86f9ae1aa68513ba1d889841122158818245b","observation_id":"4b39b26a-a2d0-4d03-a627-b7361f8af37e","resolution":{"observed_at":"2026-05-11T16:46:21.588455Z","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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:3d039af5e59362150e8a470125e339c8e85a7eb09f19c4cb29415fae3aadf945","observation_id":"7a4197f8-9f7c-4ed0-8945-65e5f2a5a3f0","resolution":{"observed_at":"2026-05-11T16:51:05.221878Z","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":"2507.08390","last_updated":"2026-04-08T07:40:07Z","snapshot_observed_at":"2026-07-06T21:55:31.588385Z","submitted_at":"2025-07-11T08:00:47Z","title":"Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement","version":4},"cited_work":{"arxiv_id":"2507.08390","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.08390","snapshot_observed_at":"2026-07-03T13:48:21.273527Z","title":"Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement","venue":"cs.LG","work_id":"9c59910b-3e7a-46e0-9039-0ef35ba0f2ad","year":2025},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2507.08390","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:acff31975ab7c1144cf37166f9e99e848e1d347e64a265f767f7e6d587ca2255","observation_id":"bae7afe8-6caa-47e4-812b-6f3c4f014cde","resolution":{"observed_at":"2026-05-11T16:46:21.564305Z","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":"2211.15089","last_updated":"2022-12-15T14:27:19Z","snapshot_observed_at":"2026-07-06T14:23:43.235725Z","submitted_at":"2022-11-28T06:08:54Z","title":"Continuous diffusion for categorical data","version":3},"cited_work":{"arxiv_id":"2211.15089","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.15089","snapshot_observed_at":"2026-07-04T17:09:58.816805Z","title":"Continuous diffusion for categorical data","venue":"cs.CL","work_id":"c0904b65-a618-46bd-85ef-53635f43ea5c","year":2022},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2211.15089","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:927e43385fd7309498664872edd482774f41e77950cac9545c189336260f6eaf","observation_id":"95a89aa2-d6e0-4f4e-a881-a3f313f47884","resolution":{"observed_at":"2026-05-18T03:30:22.553521Z","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":"2604.00375","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Locally confident, globally stuck: The quality-exploration dilemma in diffusion language models.arXiv preprint arXiv:2604.00375","venue":null,"work_id":"4b255922-04df-47d1-a33b-157c12f538bc","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:aaf7a14cc837859af48b01c1094f9e0fc9df5390a2d8ecbbf9e2e781c5b47786","observation_id":"442a306e-d7ac-4d93-a63f-91e22777413f","resolution":{"observed_at":"2026-05-11T16:46:22.854730Z","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":"2404.03683","last_updated":"2024-04-01T06:50:52Z","snapshot_observed_at":"2026-08-04T06:04:31.248459Z","submitted_at":"2024-04-01T06:50:52Z","title":"Stream of Search (SoS): Learning to Search in Language","version":1},"cited_work":{"arxiv_id":"2404.03683","doi":"10.48550/arxiv.2404.03683","metadata_source":"pith","pith_arxiv_id":"2404.03683","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Stream of search (sos): Learning to search in language","venue":"cs.LG","work_id":"a07f8e1c-30f0-4943-bb3c-40ea42cde6c7","year":2024},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2404.03683","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:c92a874d93c8ceb1695e841a1331dd22b9d30a6ba523568eef07d2961d2a1231","observation_id":"32d7e71e-4279-4270-b634-edd30d2b1abf","resolution":{"observed_at":"2026-05-11T16:51:05.305971Z","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":"2026-07-09T10:48:37.268371+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T10:48:37.268371+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17891","last_updated":"2025-05-31T07:01:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-23T14:04:22Z","title":"Scaling Diffusion Language Models via Adaptation from Autoregressive Models","version":3},"cited_work":{"arxiv_id":"2410.17891","doi":"10.48550/arxiv.2410.17891","metadata_source":"pith","pith_arxiv_id":"2410.17891","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling Diffusion Language Models via Adaptation from Autoregressive Models","venue":"cs.CL","work_id":"48644013-438b-4fbc-a954-11e2c6f91808","year":2024},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2410.17891","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:4a88a1a49a810e858f1b4c981338bbd019d2f3d507198dc6f7adf22961426ae0","observation_id":"6f4ee7cb-c677-4cd1-8e4a-8f658937c9d8","resolution":{"observed_at":"2026-05-20T19:59:37.219442Z","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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2103.03874","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:cb9922de8e19bf054b7fa5eb6933b73bd8f0b5c5109f2f814e013ba8b9c0b26f","observation_id":"2a69ebb6-3776-4db9-adc7-cdbb592433f4","resolution":{"observed_at":"2026-05-11T16:46:22.289344Z","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":{"arxiv_id":"2207.12598","last_updated":"2022-07-26T01:42:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-07-26T01:42:07Z","title":"Classifier-Free Diffusion Guidance","version":1},"cited_work":{"arxiv_id":"2207.12598","doi":"10.1109/cvpr52733.2024.02494","metadata_source":"pith","pith_arxiv_id":"2207.12598","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Classifier-Free Diffusion Guidance","venue":"cs.LG","work_id":"acf2c588-c088-4a6c-938e-150ad7c666d7","year":2022},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:3b29791dee6615aa8d7c3a808252a731be1221aeb8ab6aac56289c7f05bde00b","observation_id":"35de0174-22e5-40ab-8205-537804244596","resolution":{"observed_at":"2026-05-11T16:51:05.264941Z","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":"2509.23653","doi":"10.48550/arxiv.2509.23653","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Don’t settle too early: Self-reflective remasking for diffusion language models.arXiv preprint arXiv:2509.23653","venue":"arXiv (Cornell University)","work_id":"4f021da2-431e-4336-bd78-958edfe02200","year":2021},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:39e367c2a5d8ff9e38a6f103475ddb4e94689cfdcc3f600ca965e67d2691ddcc","observation_id":"45bd7eed-dd5c-41ad-8664-7b26a2153f30","resolution":{"observed_at":"2026-05-11T16:51:05.273244Z","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":"2502.06079","last_updated":"2025-09-01T20:58:35Z","snapshot_observed_at":"2026-07-06T20:33:39.014448Z","submitted_at":"2025-02-10T00:27:54Z","title":"Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo","version":3},"cited_work":{"arxiv_id":"2502.06079","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06079","snapshot_observed_at":"2026-07-02T15:37:06.069204Z","title":"Debiasing guidance for discrete diffusion with sequential monte carlo","venue":null,"work_id":"ee7fcfa6-2a4b-4015-8819-52904379362b","year":2025},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2502.06079","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:e92d4fecd4b4bfcad5810ff665e36baf8a4f7b174f29b3551c84fe2c8973b369","observation_id":"5b508757-0f7d-411f-a3ef-e127b47f654a","resolution":{"observed_at":"2026-05-11T16:46:22.488766Z","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":"2505.20199","last_updated":"2025-05-26T16:40:22Z","snapshot_observed_at":"2026-07-06T21:30:46.863005Z","submitted_at":"2025-05-26T16:40:22Z","title":"Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking","version":1},"cited_work":{"arxiv_id":"2505.20199","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.20199","snapshot_observed_at":"2026-07-03T20:18:57.809059Z","title":"Adaptive classifier-free guidance via dynamic low-confidence masking.arXiv preprint arXiv:2505.20199, 2025a","venue":null,"work_id":"e9db92ca-8543-4ee8-84b9-310145f99a77","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2505.20199","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:a9db79d4a123517c9929e41d8d78f04d6407034cdbe8f535f629ffdfb1040e34","observation_id":"4595b529-7ded-4409-a460-a455aad89d89","resolution":{"observed_at":"2026-05-11T16:46:23.314797Z","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":"Diffusion guided language modeling","venue":null,"work_id":"11a6dab1-af4f-4992-a5b1-2f9ebb8f9d69","year":2024},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:9bfa0b1e713ab93d4c98a4722476fd930864d18cd3f43176139756b8f8020da1","observation_id":"198457f5-74bf-4300-a048-57305ec38bba","resolution":{"observed_at":"2026-05-26T01:36:29.259154Z","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":"2602.05992","last_updated":"2026-06-17T04:52:05Z","snapshot_observed_at":"2026-08-03T04:07:41.584536Z","submitted_at":"2026-02-05T18:41:38Z","title":"DSB: Dynamic Sliding Block Scheduling for Diffusion LLMs","version":3},"cited_work":{"arxiv_id":"2602.05992","doi":null,"metadata_source":"pith","pith_arxiv_id":"2602.05992","snapshot_observed_at":"2026-07-03T21:18:59.380248Z","title":"Dsb: Dynamic sliding block scheduling for diffusion llms.arXiv preprint arXiv:2602.05992","venue":"cs.CL","work_id":"bec8d744-ca5d-43ea-9905-2e52eab1ecca","year":2026},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2602.05992","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:9b50f353358b3907279e3f6820a0db2f898ab84f8ffecac4c32a5eb4d6a97dc0","observation_id":"515a3135-5ddc-4813-a756-adfff2586b4d","resolution":{"observed_at":"2026-06-19T17:10:49.357944Z","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":"2603.15803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mask is what dllm needs: A masked data training paradigm for diffusion llms.arXiv preprint arXiv:2603.15803","venue":null,"work_id":"c94c0434-a479-4ac1-92e4-3b96c7dcf6fc","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:115fa4c44f8daca7178378c337a807d03f658dae6a34391b26f559adc8fa12e8","observation_id":"dce92fb1-2c43-4239-aea4-c997f81924af","resolution":{"observed_at":"2026-05-11T16:46:21.788600Z","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":"2512.04135","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T22:52:44.925567Z","title":"Decoding large language diffusion models with foreseeing movement.arXiv preprint arXiv:2512.04135","venue":null,"work_id":"9a2200ba-9a1d-487c-92a2-e7337e2e52c9","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:98c99e3a15f2353791f4946978571db5dc3e0fae3d5c3d5d51eb4f7adf70de75","observation_id":"bb4a4a1b-0ac1-4693-a199-1f46df8e14f9","resolution":{"observed_at":"2026-05-11T16:46:21.926515Z","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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2502.09992","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:134608dacea45b0e81d0ac099a05880266e994f7c0a3ed0c2bba0aba5f04e678","observation_id":"c87c49f0-f142-4067-aa60-f7ace27a3b88","resolution":{"observed_at":"2026-05-11T16:51:05.252747Z","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":null,"venue":null,"work_id":"f3b534f2-238f-4687-9aca-7b61e01f8ef9","year":2021},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:6b9fb0d474f2c8e62e0617e8533cb50bba6babea466fc048f28253f9bb18c043","observation_id":"cbbd3274-67b2-4f34-ad19-b85c64b8442e","resolution":{"observed_at":"2026-05-26T01:36:29.256149Z","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":"2508.09138","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T13:58:21.250281Z","title":"Qingyan Wei, Yaojie Zhang, Zhiyuan Liu, Dongrui Liu, and Linfeng Zhang","venue":null,"work_id":"e614108d-9051-461d-a6ed-8410559b263d","year":2025},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:e4d4c38ef54b61f3773590a24b3404cd8c10c565bb62a4a9a056d3040a97adb2","observation_id":"f82eec0c-6a4b-490e-9c53-0d880191c33e","resolution":{"observed_at":"2026-05-11T16:46:22.725985Z","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":"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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:304fd04a5bd1092a8f59e7d5684f818acc605a997a8b997740c5a5e58b761fa7","observation_id":"fd31f20f-0327-41b0-a5ed-1571556980aa","resolution":{"observed_at":"2026-05-11T16:51:05.238375Z","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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2505.22618","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:f2ed175200e206881eab1e8168c18f8b2483fdd9787985e28930c982a8ee3cdc","observation_id":"d507f685-85de-486f-97f1-8560483e4d0d","resolution":{"observed_at":"2026-05-16T04:28:02.518107Z","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":"2026-05-25T17:53:19.96554+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":"2601.22629","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-annealed perturbation sampling: Diverse generation for diffusion language models.arXiv preprint arXiv:2601.22629","venue":null,"work_id":"e2a186f5-1b08-46be-b5a9-6ade47e62f93","year":null},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:b04a0afc40d1224d60d922d08a150431fb4c93fb2cda7f050a2c4ff0ecc4357a","observation_id":"eda0b9a8-b679-4b51-aeae-4c179a44c356","resolution":{"observed_at":"2026-05-11T16:46:22.748341Z","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":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2508.15487","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:611bbeccd50f98c858ba744d3acd748bcd733d361467341b5f67565d8197a441","observation_id":"b19090c8-7d93-4e93-a3d4-73593eb6fc21","resolution":{"observed_at":"2026-05-11T16:46:23.134278Z","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":"2604.08964","last_updated":"2026-04-10T05:08:39Z","snapshot_observed_at":"2026-08-02T14:44:29.273173Z","submitted_at":"2026-04-10T05:08:39Z","title":"Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models","version":1},"cited_work":{"arxiv_id":"2604.08964","doi":"10.48550/arxiv.2604.08964","metadata_source":"pith","pith_arxiv_id":"2604.08964","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models","venue":"cs.CL","work_id":"f6a59c76-35bb-4b95-99a5-0f47c546ef5c","year":2026},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"cited_paper":"/paper/2604.08964","citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:7df93c84faa8ed0a5cc334d9c3d5dc77a4b62965bcd0e5a6549afb68c495a10d","observation_id":"caf1c025-8f85-4733-b3c7-6fe00a6e9eec","resolution":{"observed_at":"2026-05-11T16:46:23.325802Z","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":null,"venue":null,"work_id":"40052b57-3fc9-46a5-aa12-a07b0b4d7118","year":2023},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:f9731babcf3b57ed9a14425728ca0187e9402d1a4894d5804bf348903e84311b","observation_id":"ced0d513-5db4-406d-9b5d-d62a397a8a67","resolution":{"observed_at":"2026-05-26T01:36:29.262054Z","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":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":"841c6e20-5498-4bdc-bdd2-e26f97e06f5f","year":2025},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:47edcfd5ad5f707bae62cec30bf707263a59e2119dd4e26e98f74b4ea42beba4","observation_id":"dee4acd8-0553-4955-b9ae-5796a9ea8374","resolution":{"observed_at":"2026-05-26T01:36:29.265092Z","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":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Datasets: •GSM8K[Cobbe et al., 2021]: MIT License","venue":null,"work_id":"356d8e46-03b0-4067-82fd-3fe3ba5dd973","year":2025},"citing_paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-09T14:59:49.792976Z"},"links":{"citing_paper":"/paper/2605.01373"},"observation_digest":"sha256:f0d180fe69072315d895fe39c9036e94db934d640df1edf8e45e389c58ffaaf7","observation_id":"97bbc998-27e8-45cc-b027-af2a93947599","resolution":{"observed_at":"2026-05-26T01:36:29.253434Z","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"}}],"paper":{"arxiv_id":"2605.01373","last_updated":"2026-05-02T10:46:56Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-02T10:46:56Z","title":"Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":3,"verified_exact":24,"verified_fuzzy":3},"total_outbound_references":32},"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 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2605.01373."}