{"as_of":"2026-08-08T09:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6995bb20549fe4769c75bc3b6a7495c1359e0d1650665acbc9ec8a2b7a33590a","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T10:17:25.325009Z","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":"2026-05-19T22:12:51.008075Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-08-07T10:17:25.325009Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05939","last_updated":"2025-06-06T10:07:21Z","snapshot_observed_at":"2026-08-08T00:35:54.760568Z","submitted_at":"2025-06-06T10:07:21Z","title":"Respecting Temporal-Causal Consistency: Entity-Event Knowledge Graphs for Retrieval-Augmented Generation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T10:17:25.325009Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2506.05939"},"observation_digest":"sha256:905f1a2bf2801cbe664e3aae82d702dbf2f50b513df0ed75d912fbbf1caed299","observation_id":"be746002-2e1c-4d27-b862-2eb1cef935c5","resolution":{"observed_at":"2026-08-07T10:17:25.325009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-08-06T23:49:45.997697Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.16024","last_updated":"2025-06-19T04:44:34Z","snapshot_observed_at":"2026-08-06T23:42:02.504756Z","submitted_at":"2025-06-19T04:44:34Z","title":"From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T23:49:45.997697Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2506.16024"},"observation_digest":"sha256:4cec0c7ad22491f5365b928f070ed8710dd7082f572cb70b15e8b1a81c69f52c","observation_id":"086c634b-f677-4d9c-8c9a-9cef0dbeb295","resolution":{"observed_at":"2026-08-06T23:49:45.997697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-08-06T14:56:12.142185Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17290","last_updated":"2025-07-23T07:51:56Z","snapshot_observed_at":"2026-08-06T14:49:28.402006Z","submitted_at":"2025-07-23T07:51:56Z","title":"Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T14:56:12.142185Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2507.17290"},"observation_digest":"sha256:7c058205b567b8d40d9ddc600941ef2311cb01d5a40ce42483acf25f07329bee","observation_id":"305ee485-0657-43f4-acad-4f47ff81aa97","resolution":{"observed_at":"2026-08-06T14:56:12.142185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-08-03T05:43:53.995030Z","title":"Longgenbench: Long-context generation benchmark.arXiv preprint arXiv:2410.04199,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.01472","last_updated":"2026-06-24T08:53:47Z","snapshot_observed_at":"2026-08-03T05:43:51.520535Z","submitted_at":"2026-02-01T22:31:19Z","title":"ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T05:43:53.995030Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2602.01472"},"observation_digest":"sha256:29eaafbd254f5501cbf668e6c782debd82d2235019079c5ec06320f9b206a988","observation_id":"89828279-84e9-4a30-81ad-99a0ab36b36e","resolution":{"observed_at":"2026-08-03T05:43:53.995030Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":"2410.04199","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"aa387da9-5c4f-4b35-80dc-02226db0fa98","year":2024},"citing_paper":{"arxiv_id":"2604.26837","last_updated":"2026-04-29T16:02:00Z","snapshot_observed_at":"2026-07-06T23:12:24.456023Z","submitted_at":"2026-04-29T16:02:00Z","title":"Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-07T13:15:21.201950Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2604.26837"},"observation_digest":"sha256:4481c507f35009d93d5115a50290762f98a9b489fcd326cebe3f26fe57ae14bd","observation_id":"4f246729-f06f-4778-b412-00e01429ed6d","resolution":{"observed_at":"2026-05-12T09:01:25.908782Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":"2410.04199","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"aa387da9-5c4f-4b35-80dc-02226db0fa98","year":2024},"citing_paper":{"arxiv_id":"2605.10039","last_updated":"2026-05-11T06:09:47Z","snapshot_observed_at":"2026-08-03T02:44:36.380393Z","submitted_at":"2026-05-11T06:09:47Z","title":"Instruction Adherence in Coding Agent Configuration Files: A Factorial Study of Four File-Structure Variables","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-12T02:42:07.091384Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2605.10039"},"observation_digest":"sha256:71f5435409dad1ddcfae35e7db5a1829bcb3ad993581498f691dce236eeaaa53","observation_id":"2224b735-4a8b-4e31-aa58-8fe815357dae","resolution":{"observed_at":"2026-05-12T07:31:26.096019Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark","version":3},"cited_work":{"arxiv_id":"2410.04199","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04199","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"aa387da9-5c4f-4b35-80dc-02226db0fa98","year":2024},"citing_paper":{"arxiv_id":"2605.17613","last_updated":"2026-05-17T19:18:39Z","snapshot_observed_at":"2026-07-06T23:28:36.134614Z","submitted_at":"2026-05-17T19:18:39Z","title":"VeriCache: Turning Lossy KV Cache into Lossless LLM Inference","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-19T22:09:15.782104Z"},"links":{"cited_paper":"/paper/2410.04199","citing_paper":"/paper/2605.17613"},"observation_digest":"sha256:59d2a1c81093dfce729afc9abcec99745fae4f3339d46dc9ba9a9d92e5e4362c","observation_id":"c0690b1c-f15b-4904-b630-c3fb5281cea9","resolution":{"observed_at":"2026-05-19T22:12:51.011084Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.04199/citation-record","integrity":"/paper/2410.04199/integrity","json":"/paper/2410.04199/citation-record.json","paper":"/paper/2410.04199"},"outbound":[],"paper":{"arxiv_id":"2410.04199","last_updated":"2024-10-24T14:43:22Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T04:56:00.906905Z","submitted_at":"2024-10-05T15:33:25Z","title":"LongGenBench: Long-context Generation Benchmark"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.04199."}