{"as_of":"2026-08-08T10:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:18860dceae15a702eec84d71a1931776bc28fb382f01758c68e99ba8b087f55d","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:45:07.680865Z","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":"2026-06-30T13:54:44.090606Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.11972","last_updated":"2026-05-29T09:22:41Z","snapshot_observed_at":"2026-08-07T16:01:50.853660Z","submitted_at":"2025-04-16T11:08:46Z","title":"Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.11972","snapshot_observed_at":"2026-08-06T21:45:07.680865Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.23864","last_updated":"2025-06-30T13:57:28Z","snapshot_observed_at":"2026-08-07T23:55:18.987455Z","submitted_at":"2025-06-30T13:57:28Z","title":"Garbage In, Reasoning Out? Why Benchmark Scores are Unreliable and What to Do About It","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T21:45:07.680865Z"},"links":{"cited_paper":"/paper/2504.11972","citing_paper":"/paper/2506.23864"},"observation_digest":"sha256:9f65380090ae546f53f52ab285aaff1d47beaf9204a5a9c97232924abaa31848","observation_id":"22ed2e5a-77d4-4f14-a3c5-255b268485e6","resolution":{"observed_at":"2026-08-06T21:45:07.680865Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.11972","last_updated":"2026-05-29T09:22:41Z","snapshot_observed_at":"2026-08-07T16:01:50.853660Z","submitted_at":"2025-04-16T11:08:46Z","title":"Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.11972","snapshot_observed_at":"2026-08-06T17:09:21.645814Z","title":"Llm-as-a-judge: Reassessing the performance of llms in ex- tractive qa","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.11968","last_updated":"2025-07-16T07:02:15Z","snapshot_observed_at":"2026-08-07T07:48:36.747502Z","submitted_at":"2025-07-16T07:02:15Z","title":"Watch, Listen, Understand, Mislead: Tri-modal Adversarial Attacks on Short Videos for Content Appropriateness Evaluation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:09:21.645814Z"},"links":{"cited_paper":"/paper/2504.11972","citing_paper":"/paper/2507.11968"},"observation_digest":"sha256:c8730de4bb2ef80767f9a47f44861d9b4437301b969d2aa3dc3b017f8eea42d0","observation_id":"85cf70de-8463-44ab-83dd-6938be8f6a6d","resolution":{"observed_at":"2026-08-06T17:09:21.645814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.11972","last_updated":"2026-05-29T09:22:41Z","snapshot_observed_at":"2026-08-07T16:01:50.853660Z","submitted_at":"2025-04-16T11:08:46Z","title":"Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses","version":3},"cited_work":{"arxiv_id":"2504.11972","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.11972","snapshot_observed_at":"2026-06-30T13:54:44.090606Z","title":"Llm-as-a-judge: Reassessing the performance of llms in extractive qa","venue":"cs.CL","work_id":"135d88c8-3b58-431d-8fa2-7cdc50d00b03","year":2025},"citing_paper":{"arxiv_id":"2604.09791","last_updated":"2026-04-10T18:13:09Z","snapshot_observed_at":"2026-07-06T22:58:34.504325Z","submitted_at":"2026-04-10T18:13:09Z","title":"Pioneer Agent: Continual Improvement of Small Language Models in Production","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-05-10T17:48:40.520740Z"},"links":{"cited_paper":"/paper/2504.11972","citing_paper":"/paper/2604.09791"},"observation_digest":"sha256:3004d550d377cc520e743935ef4bea9b78f72d37e1a0f33bd843a28034bb55cf","observation_id":"cdecac83-b372-4463-af7c-81e53c2ddf6f","resolution":{"observed_at":"2026-06-01T02:02:15.555696Z","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":"2504.11972","last_updated":"2026-05-29T09:22:41Z","snapshot_observed_at":"2026-08-07T16:01:50.853660Z","submitted_at":"2025-04-16T11:08:46Z","title":"Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses","version":3},"cited_work":{"arxiv_id":"2504.11972","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.11972","snapshot_observed_at":"2026-06-30T13:54:44.090606Z","title":"Llm-as-a-judge: Reassessing the performance of llms in extractive qa","venue":"cs.CL","work_id":"135d88c8-3b58-431d-8fa2-7cdc50d00b03","year":2025},"citing_paper":{"arxiv_id":"2605.24366","last_updated":"2026-05-23T03:07:33Z","snapshot_observed_at":"2026-07-06T23:34:28.608412Z","submitted_at":"2026-05-23T03:07:33Z","title":"Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T13:46:36.001392Z"},"links":{"cited_paper":"/paper/2504.11972","citing_paper":"/paper/2605.24366"},"observation_digest":"sha256:d5e40523139d825fa6384f0e5262ea8bbf4b8f5f54de8d1cc249271808bad6c2","observation_id":"2b17e019-f3a0-43d1-a088-3146e0c0edaa","resolution":{"observed_at":"2026-06-30T13:54:44.091820Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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/2504.11972/citation-record","integrity":"/paper/2504.11972/integrity","json":"/paper/2504.11972/citation-record.json","paper":"/paper/2504.11972"},"outbound":[],"paper":{"arxiv_id":"2504.11972","last_updated":"2026-05-29T09:22:41Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T16:01:50.853660Z","submitted_at":"2025-04-16T11:08:46Z","title":"Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses"},"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 4 inbound Pith citation observations for arXiv:2504.11972."}