{"as_of":"2026-08-14T02:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2947ace3901bbd0e129018f05ebf4d08b9a6f7538e621b26abb86a14dd2bf8a6","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T16:21:05.570023Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","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":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_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},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-05-11T01:42:54.279353Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2502.09992"},"observation_digest":"sha256:f998aa66569826ac4e3d2d4078c3d1dbfce28806f505416f9b34588438ad0f0d","observation_id":"bc26bfea-5dc3-4f44-9d86-34837075bbbf","resolution":{"observed_at":"2026-05-11T01:42:54.719344Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2602.16813","last_updated":"2026-05-20T16:23:05Z","snapshot_observed_at":"2026-08-11T06:21:47.511868Z","submitted_at":"2026-02-18T19:23:07Z","title":"Flow Map Language Models: One-step Language Modeling via Continuous Denoising","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-15T21:01:42.916835Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2602.16813"},"observation_digest":"sha256:0533a40c9441f7f72b8f6c751f7ec6103a271a38e32a1453e7fc1101df2ba182","observation_id":"e37429d7-1032-4167-a03f-e9c5e98a4b29","resolution":{"observed_at":"2026-05-15T21:10:19.141467Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2602.16813","last_updated":"2026-05-20T16:23:05Z","snapshot_observed_at":"2026-08-11T06:21:47.511868Z","submitted_at":"2026-02-18T19:23:07Z","title":"Flow Map Language Models: One-step Language Modeling via Continuous Denoising","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T12:23:49.031978Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2602.16813"},"observation_digest":"sha256:029e7ee2b2f0791ca98f5fe37cc8135a9e83a0e2e947c329010b8ce8887bacf6","observation_id":"1aeaff85-221e-4b12-87eb-5c0553652acb","resolution":{"observed_at":"2026-05-21T12:24:10.605784Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2605.07193","last_updated":"2026-05-08T03:40:39Z","snapshot_observed_at":"2026-08-11T17:09:33.591621Z","submitted_at":"2026-05-08T03:40:39Z","title":"Coupling Models for One-Step Discrete Generation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-11T02:58:10.909499Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2605.07193"},"observation_digest":"sha256:7360d506d610a562e7889f216ab8c615bfff97a5e97e3610d079f849aebed7ad","observation_id":"07fb5646-7750-4275-acf7-7676e53fc0b1","resolution":{"observed_at":"2026-05-11T03:00:54.926138Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2605.21484","last_updated":"2026-05-20T17:59:10Z","snapshot_observed_at":"2026-08-01T17:24:17.193550Z","submitted_at":"2026-05-20T17:59:10Z","title":"One-Step Distillation of Discrete Diffusion Image Generators via Fixed-Point Iteration","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-21T04:37:09.279620Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2605.21484"},"observation_digest":"sha256:be98cd175b0a0829fb3a5a8529d102f2948c9703beb11636fa48b1dccceddaa2","observation_id":"89c5e0bf-4983-4d32-b092-9405758c4c09","resolution":{"observed_at":"2026-05-21T04:39:35.185911Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2605.31215","last_updated":"2026-05-29T12:19:26Z","snapshot_observed_at":"2026-08-13T07:12:11.042695Z","submitted_at":"2026-05-29T12:19:26Z","title":"Fixed-Point Masked Generative Modeling","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-28T23:18:27.050697Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2605.31215"},"observation_digest":"sha256:9e752c562df5a0583cc5dae2bf65a6f1f7dfa1219b681e80a07d61027a231268","observation_id":"c401e6ec-eecc-48c2-a4f0-7e245b61b66c","resolution":{"observed_at":"2026-06-28T23:22:47.295021Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2606.24773","last_updated":"2026-06-23T16:33:13Z","snapshot_observed_at":"2026-08-12T11:55:48.946239Z","submitted_at":"2026-06-23T16:33:13Z","title":"Posterior Refinement: Fast Language Generation via Any-Order Flow Maps","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-25T23:55:07.047233Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2606.24773"},"observation_digest":"sha256:ea8605d8da7bb8be9ca5d3801b81c34b65a4d6c7a7398da116b84c68c159fb23","observation_id":"fc632806-a52e-4a8a-834c-c0957bdfac34","resolution":{"observed_at":"2026-07-04T17:09:58.802728Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2606.27617","last_updated":"2026-06-26T00:16:40Z","snapshot_observed_at":"2026-08-13T20:29:40.928847Z","submitted_at":"2026-06-26T00:16:40Z","title":"Masked Language Flow Models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-06-29T01:17:56.122002Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2606.27617"},"observation_digest":"sha256:7f913b124aaaf81af2bf9ab92f8a86d8b6bc22014d9cda4e2a60a81818660c4d","observation_id":"98c5a126-b0b8-4cec-ae9a-e9c177420a2d","resolution":{"observed_at":"2026-07-01T19:06:02.634596Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":"2410.21035","doi":"10.48550/arxiv.2410.21035","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond autoregression: Fast llms via self-distillation through time","venue":"arXiv (Cornell University)","work_id":"0faddcd9-4a17-48fb-9592-f7095c566769","year":2024},"citing_paper":{"arxiv_id":"2607.00714","last_updated":"2026-07-01T10:02:20Z","snapshot_observed_at":"2026-07-07T00:06:20.346610Z","submitted_at":"2026-07-01T10:02:20Z","title":"Self-conditioned Flow Map Language Models via Fixed-point Flows","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-02T13:01:21.252611Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2607.00714"},"observation_digest":"sha256:1ffe839e4eb85c03313a0755c7b5b55dac82edc8cf070af07be17496d4937abb","observation_id":"d8b23d82-c155-430d-a5b5-c529d5f72f0e","resolution":{"observed_at":"2026-07-02T13:06:58.593012Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-07-11T13:03:39.236118Z","title":"arXiv preprint arXiv:2410.21035 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04819","last_updated":"2026-07-13T09:12:14Z","snapshot_observed_at":"2026-08-13T16:53:06.345450Z","submitted_at":"2026-07-06T08:51:22Z","title":"Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-11T13:03:39.236118Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2607.04819"},"observation_digest":"sha256:99e6cd9317c9be7969951e3f8180f2083195c209ed047cbce54e6598d9420a8d","observation_id":"3a740cb6-c217-49ba-b5e4-018a83d485bf","resolution":{"observed_at":"2026-07-11T13:03:39.236118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21035","snapshot_observed_at":"2026-07-14T16:21:05.570023Z","title":"arXiv preprint arXiv:2410.21035 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04819","last_updated":"2026-07-13T09:12:14Z","snapshot_observed_at":"2026-08-13T16:53:06.345450Z","submitted_at":"2026-07-06T08:51:22Z","title":"Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-14T16:21:05.570023Z"},"links":{"cited_paper":"/paper/2410.21035","citing_paper":"/paper/2607.04819"},"observation_digest":"sha256:414ae4a828fc5aafa066e9b1a7fd3920272dd2e44667280b55bd1208e9a3cc63","observation_id":"1c6bdeff-f391-4feb-a16e-5c0487b1ee1b","resolution":{"observed_at":"2026-07-14T16:21:05.570023Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.21035/citation-record","integrity":"/paper/2410.21035/integrity","json":"/paper/2410.21035/citation-record.json","paper":"/paper/2410.21035"},"outbound":[],"paper":{"arxiv_id":"2410.21035","last_updated":"2025-02-06T20:26:24Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T22:13:46.678873Z","submitted_at":"2024-10-28T13:56:30Z","title":"Beyond Autoregression: Fast LLMs via Self-Distillation Through Time"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.21035."}