{"as_of":"2026-08-11T13:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:53ea1eeb98eac29c47f59e2674e3963c17805119d9ca4200c8ee629832794683","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T12:18:19.431265Z","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":"2026-05-18T10:11:14.624101Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":"2310.05869","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hyperattention: Long-context attention in near-linear time","venue":null,"work_id":"39d0b1c1-6b2a-48b4-8989-17e14b839afb","year":2023},"citing_paper":{"arxiv_id":"2306.14048","last_updated":"2023-12-18T19:10:00Z","snapshot_observed_at":"2026-08-06T19:19:02.165567Z","submitted_at":"2023-06-24T20:11:14Z","title":"H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models","version":3},"reference_index":108,"source":"pdf_text","source_observed_at":"2026-05-17T18:00:50.053377Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2306.14048"},"observation_digest":"sha256:8f4bac001a5c0e96f2024b4f8a3cedac776dd7b99c045a02d8fc15b5df472bbf","observation_id":"5205dbb1-5318-4ccc-8b02-3f3ba5b7a369","resolution":{"observed_at":"2026-05-17T18:00:50.306582Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-08-11T12:18:19.431265Z","title":"P., and Zandieh, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.14468","last_updated":"2025-06-03T21:55:57Z","snapshot_observed_at":"2026-08-11T12:10:25.114930Z","submitted_at":"2024-12-19T02:34:15Z","title":"HashAttention: Semantic Sparsity for Faster Inference","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T12:18:19.431265Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2412.14468"},"observation_digest":"sha256:5424c3a81163824ce978876592ef44b515bd1a08d860f35b774b7c23c2c8a003","observation_id":"8b9c8b8a-f05c-4a21-8f93-26c9a3df6f0a","resolution":{"observed_at":"2026-08-11T12:18:19.431265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-08-10T14:58:40.299668Z","title":"Hyperattention: Long-context attention in near- linear time","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.14679","last_updated":"2025-02-20T07:37:41Z","snapshot_observed_at":"2026-08-10T14:52:42.105410Z","submitted_at":"2025-01-24T17:57:06Z","title":"Surface Vision Mamba: Leveraging Bidirectional State Space Model for Efficient Spherical Manifold Representation","version":5},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T14:58:40.299668Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2501.14679"},"observation_digest":"sha256:e21a175875272552fffea032bcfc60937f875fe1ed0ad06640b403883ada41c5","observation_id":"756053e9-c287-4a06-8bfd-31859cef7a98","resolution":{"observed_at":"2026-08-10T14:58:40.299668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-08-09T18:51:12.456504Z","title":"Hyperattention: Long-context attention in near-linear time","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.00500","last_updated":"2025-02-04T15:19:12Z","snapshot_observed_at":"2026-08-10T02:49:33.781140Z","submitted_at":"2025-02-01T17:40:11Z","title":"Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T18:51:12.456504Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2502.00500"},"observation_digest":"sha256:dfe2699a0b2f492729772aa5dbb398fc37b4cc9c2a11bbd7d2a0c4f296d7af56","observation_id":"38e48125-b958-4152-a2db-d651a175ad34","resolution":{"observed_at":"2026-08-09T18:51:12.456504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-08-08T05:56:55.108746Z","title":"Hyperattention: Long-context attention in near-linear time.arXiv preprint arXiv:2310.05869,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08246","last_updated":"2025-06-03T10:07:35Z","snapshot_observed_at":"2026-08-09T15:11:46.240343Z","submitted_at":"2025-02-12T09:39:54Z","title":"Inference-time sparse attention with asymmetric indexing","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T05:56:55.108746Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2502.08246"},"observation_digest":"sha256:417e879fed2db8e1904369b553f3efec612d581c80b70fd978926d3c4c553c34","observation_id":"15a9ccc8-b0d2-472b-9a6d-516d0b0bc9bb","resolution":{"observed_at":"2026-08-08T05:56:55.108746Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-08-06T14:59:18.324072Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17245","last_updated":"2025-07-23T06:29:38Z","snapshot_observed_at":"2026-08-06T19:10:03.852056Z","submitted_at":"2025-07-23T06:29:38Z","title":"DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T14:59:18.324072Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2507.17245"},"observation_digest":"sha256:ef97c049af54fb4df47b71e5b1061bcbc0be7204f264854f0d238448fa1e03e0","observation_id":"5214b05d-ff75-468e-be1d-1233b187f920","resolution":{"observed_at":"2026-08-06T14:59:18.324072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear Time","version":3},"cited_work":{"arxiv_id":"2310.05869","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.05869","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hyperattention: Long-context attention in near-linear time","venue":null,"work_id":"39d0b1c1-6b2a-48b4-8989-17e14b839afb","year":2023},"citing_paper":{"arxiv_id":"2510.04008","last_updated":"2026-04-18T14:33:30Z","snapshot_observed_at":"2026-07-06T22:31:44.964774Z","submitted_at":"2025-10-05T02:57:40Z","title":"RACE Attention: A Strictly Linear-Time Attention Layer for Training on Outrageously Large Contexts","version":5},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-18T10:06:28.425668Z"},"links":{"cited_paper":"/paper/2310.05869","citing_paper":"/paper/2510.04008"},"observation_digest":"sha256:a8aaea9e0b7bce75f3ba3a5b97a53a3a5586bcda56bfa32f7a3c8498c077b5e8","observation_id":"4db5b3a9-6f7e-49a5-8393-8a533bcadf8e","resolution":{"observed_at":"2026-05-18T10:11:14.627110Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.05869/citation-record","integrity":"/paper/2310.05869/integrity","json":"/paper/2310.05869/citation-record.json","paper":"/paper/2310.05869"},"outbound":[],"paper":{"arxiv_id":"2310.05869","last_updated":"2023-12-01T17:43:06Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T16:29:55.892584Z","submitted_at":"2023-10-09T17:05:25Z","title":"HyperAttention: Long-context Attention in Near-Linear 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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.05869."}