{"as_of":"2026-08-05T23:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0a3dff7be7a54b949291ed4125e2b2dafec2115a1f55f118cba5be441143c76e","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T11:23:28.936288Z","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":"2026-05-13T23:49:10.749030Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.08719","last_updated":"2025-04-11T17:33:32Z","snapshot_observed_at":"2026-08-04T10:54:30.836473Z","submitted_at":"2025-04-11T17:33:32Z","title":"SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.08719","snapshot_observed_at":"2026-08-04T11:23:28.936288Z","title":"[PQFS23] Bowen Peng, Jeffrey Quesnelle, Honglu Fan, and Enrico Shippole","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.05554","last_updated":"2026-07-30T05:50:28Z","snapshot_observed_at":"2026-08-04T11:23:20.235263Z","submitted_at":"2025-10-07T03:51:57Z","title":"Critical attention scaling in long-context transformers","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T11:23:28.936288Z"},"links":{"cited_paper":"/paper/2504.08719","citing_paper":"/paper/2510.05554"},"observation_digest":"sha256:4db933541e6ba9e3de8657ff255208b9f201c8220120edb8ad3452744deea8bb","observation_id":"fe710e60-0889-4fe5-9610-e12dfe0d63b8","resolution":{"observed_at":"2026-08-04T11:23:28.936288Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.08719","last_updated":"2025-04-11T17:33:32Z","snapshot_observed_at":"2026-08-04T10:54:30.836473Z","submitted_at":"2025-04-11T17:33:32Z","title":"SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling","version":1},"cited_work":{"arxiv_id":"2504.08719","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.08719","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Puvvada et al.SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling","venue":null,"work_id":"42eb1a97-9739-4f03-8883-3f639f33fe5a","year":2025},"citing_paper":{"arxiv_id":"2510.26692","last_updated":"2025-11-01T12:05:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-10-30T16:59:43Z","title":"Kimi Linear: An Expressive, Efficient Attention Architecture","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-13T23:49:10.555255Z"},"links":{"cited_paper":"/paper/2504.08719","citing_paper":"/paper/2510.26692"},"observation_digest":"sha256:5fbb7bf5068e0f61519512bd622047b9b3590135862ec46e8460e455c9b7300f","observation_id":"c93cd242-856c-464a-ac27-e9f2b15970f8","resolution":{"observed_at":"2026-05-13T23:49:10.751896Z","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":"2504.08719","last_updated":"2025-04-11T17:33:32Z","snapshot_observed_at":"2026-08-04T10:54:30.836473Z","submitted_at":"2025-04-11T17:33:32Z","title":"SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.08719","snapshot_observed_at":"2026-08-01T21:31:01.698242Z","title":"arXiv preprint arXiv:2504.08719 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16072","last_updated":"2026-07-17T15:56:52Z","snapshot_observed_at":"2026-08-05T22:03:26.987913Z","submitted_at":"2026-07-17T15:56:52Z","title":"Frontier Language Models Struggle to Copy: Text Can Be Better Viewed in 2D","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-01T21:31:01.698242Z"},"links":{"cited_paper":"/paper/2504.08719","citing_paper":"/paper/2607.16072"},"observation_digest":"sha256:0c75aa2a0f90fccb3a9fb62c4cd17b8dcb122d596165a06f7b2afcfe9a7fa606","observation_id":"ed4057f1-2743-487d-a3b3-94690b9c8024","resolution":{"observed_at":"2026-08-01T21:31:01.698242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.08719/citation-record","integrity":"/paper/2504.08719/integrity","json":"/paper/2504.08719/citation-record.json","paper":"/paper/2504.08719"},"outbound":[],"paper":{"arxiv_id":"2504.08719","last_updated":"2025-04-11T17:33:32Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T10:54:30.836473Z","submitted_at":"2025-04-11T17:33:32Z","title":"SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling"},"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":"2026-08-05T06:32:48.257954+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 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2504.08719."}