{"as_of":"2026-08-08T23:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4926345781f35cfac44b56a218a0e8739a88a0c5fbc1e4d54dfdbcf96db4abd6","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T12:11:11.763683Z","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":"2026-07-03T05:07:38.606905Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.03602","last_updated":"2024-07-27T22:01:50Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses","version":2},"cited_work":{"arxiv_id":"2404.03602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03602","snapshot_observed_at":"2026-07-03T05:07:38.606905Z","title":"Xiao Liu et al","venue":null,"work_id":"c20e9b35-2955-44b6-afa4-cd978e85eab9","year":2024},"citing_paper":{"arxiv_id":"2410.20791","last_updated":"2026-04-06T19:29:25Z","snapshot_observed_at":"2026-08-03T01:41:19.546733Z","submitted_at":"2024-10-28T07:16:00Z","title":"From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-23T19:07:21.016824Z"},"links":{"cited_paper":"/paper/2404.03602","citing_paper":"/paper/2410.20791"},"observation_digest":"sha256:e12b82df29ff70f756d0d91d58bd2cfe1a43df5da2c5f0887f60ce4023fd1e2a","observation_id":"15a2057a-aa96-4c64-b250-f091cb9ccf9c","resolution":{"observed_at":"2026-05-23T19:08:20.798545Z","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":"2404.03602","last_updated":"2024-07-27T22:01:50Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03602","snapshot_observed_at":"2026-08-07T12:11:11.763683Z","title":"Evaluating llms at de- tecting errors in llm responses,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.00309","last_updated":"2025-06-28T05:54:45Z","snapshot_observed_at":"2026-08-07T23:21:38.558900Z","submitted_at":"2025-05-30T23:37:37Z","title":"Evaluation of LLMs for mathematical problem solving","version":3},"reference_index":117,"source":"pdf_text","source_observed_at":"2026-08-07T12:11:11.763683Z"},"links":{"cited_paper":"/paper/2404.03602","citing_paper":"/paper/2506.00309"},"observation_digest":"sha256:107c1bd0ec3256936a91235711d8539059b952edcf60e76fc9a52840405fb929","observation_id":"64f61719-e4e5-41cc-8214-ee8c61b80483","resolution":{"observed_at":"2026-08-07T12:11:11.763683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03602","last_updated":"2024-07-27T22:01:50Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03602","snapshot_observed_at":"2026-08-06T18:23:29.325939Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08459","last_updated":"2025-07-11T10:02:21Z","snapshot_observed_at":"2026-08-07T21:41:40.177971Z","submitted_at":"2025-07-11T10:02:21Z","title":"Diagnosing Failures in Large Language Models' Answers: Integrating Error Attribution into Evaluation Framework","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T18:23:29.325939Z"},"links":{"cited_paper":"/paper/2404.03602","citing_paper":"/paper/2507.08459"},"observation_digest":"sha256:60d687f39b7ae8452a8386849f360f6cefd394bdb3b800e4145500ba81afb458","observation_id":"48bbf629-5b02-4954-b96c-268df6e33240","resolution":{"observed_at":"2026-08-06T18:23:29.325939Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03602","last_updated":"2024-07-27T22:01:50Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03602","snapshot_observed_at":"2026-08-05T15:18:32.971133Z","title":"Evaluating llms at detecting errors in llm responses","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.20083","last_updated":"2026-07-19T08:24:06Z","snapshot_observed_at":"2026-08-06T12:59:49.846974Z","submitted_at":"2025-08-27T17:49:28Z","title":"DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version)","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T15:18:32.971133Z"},"links":{"cited_paper":"/paper/2404.03602","citing_paper":"/paper/2508.20083"},"observation_digest":"sha256:c45a871aa44c831ac761ec09b4736741b03d2fd7f42751e47075b5e5f11c1363","observation_id":"914b416e-d7e7-40c9-b8f1-54a6eb0e3246","resolution":{"observed_at":"2026-08-05T15:18:32.971133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03602","last_updated":"2024-07-27T22:01:50Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses","version":2},"cited_work":{"arxiv_id":"2404.03602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03602","snapshot_observed_at":"2026-07-03T05:07:38.606905Z","title":"Xiao Liu et al","venue":null,"work_id":"c20e9b35-2955-44b6-afa4-cd978e85eab9","year":2024},"citing_paper":{"arxiv_id":"2606.10315","last_updated":"2026-06-09T02:11:01Z","snapshot_observed_at":"2026-08-08T21:25:41.821217Z","submitted_at":"2026-06-09T02:11:01Z","title":"Catching One in Five: LLM-as-Judge Blind Spots in Production Multi-Turn Transaction Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T13:28:08.382201Z"},"links":{"cited_paper":"/paper/2404.03602","citing_paper":"/paper/2606.10315"},"observation_digest":"sha256:7d03d4fd0e10f89e30ad5b6e70efe83c1fc9befd496e82237cfbd3b6b8ba923a","observation_id":"1a9bde0a-3b5d-4d27-a264-3d47d501b2e8","resolution":{"observed_at":"2026-07-03T05:07:38.608429Z","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/2404.03602/citation-record","integrity":"/paper/2404.03602/integrity","json":"/paper/2404.03602/citation-record.json","paper":"/paper/2404.03602"},"outbound":[],"paper":{"arxiv_id":"2404.03602","last_updated":"2024-07-27T22:01:50Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:19:47Z","title":"Evaluating LLMs at Detecting Errors in LLM Responses"},"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 5 inbound Pith citation observations for arXiv:2404.03602."}