{"as_of":"2026-08-07T19:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d18841ec2a57e8886c612652fe23b03df86e32977163b493e24ef3dc0b8a0934","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:31:44.194237Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T19:45:12.881501Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17419","snapshot_observed_at":"2026-08-07T15:31:44.194237Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02000","last_updated":"2025-06-23T01:41:05Z","snapshot_observed_at":"2026-08-07T15:25:33.498661Z","submitted_at":"2025-05-20T20:54:37Z","title":"NovelHopQA: Diagnosing Multi-Hop Reasoning Failures in Long Narrative Contexts","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T15:31:44.194237Z"},"links":{"cited_paper":"/paper/2406.17419","citing_paper":"/paper/2506.02000"},"observation_digest":"sha256:5bc55f4e84fad29033b5fc3127cc189b515645a9c58afc9e1b28a3a2ddaecd9f","observation_id":"4b1bcb33-ba5a-42d5-a058-b33a85c2f86c","resolution":{"observed_at":"2026-08-07T15:31:44.194237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17419","snapshot_observed_at":"2026-08-07T11:17:41.569413Z","title":"Leave no document behind: Benchmarking long-context llms with extended multi-doc qa","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03100","last_updated":"2025-06-09T10:35:22Z","snapshot_observed_at":"2026-08-07T11:06:27.053756Z","submitted_at":"2025-06-03T17:31:53Z","title":"Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds","version":3},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T11:17:41.569413Z"},"links":{"cited_paper":"/paper/2406.17419","citing_paper":"/paper/2506.03100"},"observation_digest":"sha256:c9c51bf31761250448aa21260dc0a9f458b698385ee65355adf61bbcbbdd8dc4","observation_id":"e661e810-7120-410f-a6a3-d2e4e31443dd","resolution":{"observed_at":"2026-08-07T11:17:41.569413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17419","snapshot_observed_at":"2026-08-07T10:17:25.351355Z","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":"2026-08-07T10:10:50.205850Z","submitted_at":"2025-06-06T10:07:21Z","title":"Respecting Temporal-Causal Consistency: Entity-Event Knowledge Graphs for Retrieval-Augmented Generation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T10:17:25.351355Z"},"links":{"cited_paper":"/paper/2406.17419","citing_paper":"/paper/2506.05939"},"observation_digest":"sha256:838f26e1af6daa9119b129f466e0d3c67b7447d9dca8e4897ca58c519d24315f","observation_id":"7133cbc0-033e-4967-b824-bd6aa81800f8","resolution":{"observed_at":"2026-08-07T10:17:25.351355Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17419","snapshot_observed_at":"2026-08-06T20:58:52.095717Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.03001","last_updated":"2025-07-02T00:53:54Z","snapshot_observed_at":"2026-08-07T17:57:05.393991Z","submitted_at":"2025-07-02T00:53:54Z","title":"Evaluating Hierarchical Clinical Document Classification Using Reasoning-Based LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:58:52.095717Z"},"links":{"cited_paper":"/paper/2406.17419","citing_paper":"/paper/2507.03001"},"observation_digest":"sha256:40d4f0bd95eba01c2f7ec7f256341dd8058b29cc563e82b53e15998cd9b4ce48","observation_id":"3b57333b-baa2-4406-9ad2-6e1dc93901c4","resolution":{"observed_at":"2026-08-06T20:58:52.095717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","version":2},"cited_work":{"arxiv_id":"2406.17419","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.17419","snapshot_observed_at":"2026-08-06T19:45:12.881501Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA","venue":"cs.CL","work_id":"ba6914a6-c1eb-4b7f-91bc-c873f17a2d44","year":2024},"citing_paper":{"arxiv_id":"2507.04723","last_updated":"2025-07-07T07:33:24Z","snapshot_observed_at":"2026-08-07T06:43:20.530023Z","submitted_at":"2025-07-07T07:33:24Z","title":"LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T19:45:12.533275Z"},"links":{"cited_paper":"/paper/2406.17419","citing_paper":"/paper/2507.04723"},"observation_digest":"sha256:7adacedb4740aee7bad2b9c3c70cce03f719fcf3ee56c4fe667805b888c5f29a","observation_id":"5fde20ef-4202-44bd-9d84-951b667df6d8","resolution":{"observed_at":"2026-08-06T19:45:12.885362Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.17419/citation-record","integrity":"/paper/2406.17419/integrity","json":"/paper/2406.17419/citation-record.json","paper":"/paper/2406.17419"},"outbound":[],"paper":{"arxiv_id":"2406.17419","last_updated":"2024-10-03T06:03:14Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T18:36:38.636181Z","submitted_at":"2024-06-25T09:42:56Z","title":"Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.17419."}