{"as_of":"2026-08-22T13:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52ec1a0bd3b4f577f2a6286ddf466e42296affe3a60d918e7ad6810145e59c24","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T17:26:36.902854Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-23T00:07:17.208973Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-08-12T10:10:29.907707Z","title":"Train short, test long: Attention with linear biases enables input length extrapolation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.19574","last_updated":"2024-12-05T12:19:38Z","snapshot_observed_at":"2026-08-15T13:09:11.103720Z","submitted_at":"2024-11-29T09:42:38Z","title":"KV Shifting Attention Enhances Language Modeling","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T10:10:29.907707Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2411.19574"},"observation_digest":"sha256:9eadf7516132f67466021a42b2d0ce4c37395504e59955b888bb0d1f0d93467d","observation_id":"0086d19a-6307-4637-bf27-29e83a48177f","resolution":{"observed_at":"2026-08-12T10:10:29.907707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":"2407.17686","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Transformers on markov data: Constant depth suffices","venue":null,"work_id":"fa1eaa12-c775-4d07-92c7-b5f93ee44576","year":2024},"citing_paper":{"arxiv_id":"2503.10574","last_updated":"2026-04-16T18:02:27Z","snapshot_observed_at":"2026-08-14T02:25:56.444963Z","submitted_at":"2025-03-13T17:24:43Z","title":"The LZ78 Source","version":4},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-23T00:06:50.969268Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2503.10574"},"observation_digest":"sha256:64ce8aee961fc313dd66b96cb1ffc0225572bce3b2465438bc6900cc6da429f4","observation_id":"8459a9ad-ffca-430c-876d-fac0d265d795","resolution":{"observed_at":"2026-05-23T00:07:17.211893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":"2407.17686","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Transformers on markov data: Constant depth suffices","venue":null,"work_id":"fa1eaa12-c775-4d07-92c7-b5f93ee44576","year":2024},"citing_paper":{"arxiv_id":"2506.07298","last_updated":"2026-04-24T00:35:40Z","snapshot_observed_at":"2026-08-11T18:19:18.277777Z","submitted_at":"2025-06-08T21:49:38Z","title":"Pre-trained Large Language Models Learn Hidden Markov Models In-context","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-19T10:34:40.987583Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2506.07298"},"observation_digest":"sha256:43906e2670cdb4cc68ee1673d97529a74e9461e173593bf2b466e2d962ec731a","observation_id":"9fecf08d-16d4-41e8-9cb5-89e804bf80de","resolution":{"observed_at":"2026-05-19T10:37:15.094419Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-08-15T17:26:36.902854Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.12837","last_updated":"2025-08-19T09:36:39Z","snapshot_observed_at":"2026-08-18T18:41:17.510354Z","submitted_at":"2025-08-18T11:24:30Z","title":"Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationary Points","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T17:26:36.902854Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2508.12837"},"observation_digest":"sha256:e912597c6848a51fb3d83bc1f3288c2c2748075d080e6198ccc34948f2b145c3","observation_id":"729f2995-ba6e-4df5-b876-53784724f649","resolution":{"observed_at":"2026-08-15T17:26:36.902854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-08-04T21:11:44.263912Z","title":"Rajaraman, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08184","last_updated":"2025-09-09T23:13:41Z","snapshot_observed_at":"2026-08-19T17:24:18.197913Z","submitted_at":"2025-09-09T23:13:41Z","title":"Selective Induction Heads: How Transformers Select Causal Structures In Context","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T21:11:44.263912Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2509.08184"},"observation_digest":"sha256:eeb24e639a0fae4237bcfcab9ef0d58093c396678417840274e1953e5b58e6b3","observation_id":"a48610f4-91f2-43b5-9bf5-8b0a5f0f1bb3","resolution":{"observed_at":"2026-08-04T21:11:44.263912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices","version":1},"cited_work":{"arxiv_id":"2407.17686","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.17686","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Transformers on markov data: Constant depth suffices","venue":null,"work_id":"fa1eaa12-c775-4d07-92c7-b5f93ee44576","year":2024},"citing_paper":{"arxiv_id":"2604.10848","last_updated":"2026-04-12T22:45:43Z","snapshot_observed_at":"2026-08-15T01:02:10.623303Z","submitted_at":"2026-04-12T22:45:43Z","title":"Transformers Learn Latent Mixture Models In-Context via Mirror Descent","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T15:22:21.955640Z"},"links":{"cited_paper":"/paper/2407.17686","citing_paper":"/paper/2604.10848"},"observation_digest":"sha256:7c3bf2aa229e245be924c566d180ae817cf35fc4c344b745311bca9d965e3fa8","observation_id":"fe242d53-4e3a-4b84-98e4-bc8ac54c0e9a","resolution":{"observed_at":"2026-05-11T10:41:05.038608Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.17686/citation-record","integrity":"/paper/2407.17686/integrity","json":"/paper/2407.17686/citation-record.json","paper":"/paper/2407.17686"},"outbound":[],"paper":{"arxiv_id":"2407.17686","last_updated":"2024-07-25T01:07:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T13:31:16.400885Z","submitted_at":"2024-07-25T01:07:09Z","title":"Transformers on Markov Data: Constant Depth Suffices"},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.17686."}