{"as_of":"2026-08-23T16:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:31f7642661c624178ed0cc17b50a518ced64ee57f938369ff64ebecc89d71b68","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":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T05:29:40.051177Z","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":"2026-05-21T22:40:43.442740Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":"2310.12558","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models help humans verify truthfulness–except when they are convincingly wrong","venue":null,"work_id":"15e9e1f1-6136-4179-95a1-00077be90b8d","year":2023},"citing_paper":{"arxiv_id":"2406.06608","last_updated":"2025-02-26T18:59:01Z","snapshot_observed_at":"2026-08-13T23:11:34.204909Z","submitted_at":"2024-06-06T18:10:11Z","title":"The Prompt Report: A Systematic Survey of Prompt Engineering Techniques","version":6},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-15T02:16:17.875268Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2406.06608"},"observation_digest":"sha256:19e94c36a9d4af7fe7c024c05c4447d87d6075479fc0960c86c0d3fc0db6fc7e","observation_id":"11270c59-8609-4c06-86b4-3fee55ede431","resolution":{"observed_at":"2026-05-15T02:16:17.904569Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-08-12T05:29:40.051177Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00372","last_updated":"2024-11-30T06:44:42Z","snapshot_observed_at":"2026-08-17T02:13:25.726849Z","submitted_at":"2024-11-30T06:44:42Z","title":"2-Factor Retrieval for Improved Human-AI Decision Making in Radiology","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:40.051177Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2412.00372"},"observation_digest":"sha256:a70200794352be92061174287438fb6be2852e4ebc9f51a20186789d8b67ece2","observation_id":"1675f972-7cf2-4a9c-b2af-aa930c7e7277","resolution":{"observed_at":"2026-08-12T05:29:40.051177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-08-10T14:57:05.737005Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16382","last_updated":"2025-01-24T18:16:53Z","snapshot_observed_at":"2026-08-20T07:37:15.556712Z","submitted_at":"2025-01-24T18:16:53Z","title":"GraPPI: A Retrieve-Divide-Solve GraphRAG Framework for Large-scale Protein-protein Interaction Exploration","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-10T14:57:05.737005Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2501.16382"},"observation_digest":"sha256:15eb3874750d8844dbd1a835c789321b76b3e064fb1d633a1a3fd44aca1854d7","observation_id":"c74eb6c4-5ff9-45d8-916a-5f207499ad82","resolution":{"observed_at":"2026-08-10T14:57:05.737005Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-08-10T14:43:55.618908Z","title":"”Large Language Models Help Humans Verify Truthfulness–Except When They Are Convincingly Wrong.” arXiv preprint arXiv:2310.12558 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.15714","last_updated":"2025-01-25T04:18:35Z","snapshot_observed_at":"2026-08-18T18:55:48.650286Z","submitted_at":"2025-01-25T04:18:35Z","title":"TrustDataFilter:Leveraging Trusted Knowledge Base Data for More Effective Filtering of Unknown Information","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T14:43:55.618908Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2502.15714"},"observation_digest":"sha256:fb7fff2c34cb7e3d7d96db976dde128b75539d76f15921a85858fbe4bbb5173d","observation_id":"311a8851-592a-44ec-9d78-05e9117f7428","resolution":{"observed_at":"2026-08-10T14:43:55.618908Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-08-07T05:28:11.165754Z","title":"T., Zhao, C., Feng, S., Daumé III, H., and Boyd-Graber, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07947","last_updated":"2025-06-09T17:11:07Z","snapshot_observed_at":"2026-08-16T05:42:28.140890Z","submitted_at":"2025-06-09T17:11:07Z","title":"Statistical Hypothesis Testing for Auditing Robustness in Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:28:11.165754Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2506.07947"},"observation_digest":"sha256:6deed76d25eaf2e2ee5df8e66c758b5c996aa7de3d04f8665470a79c5f7a9c91","observation_id":"2cd5e4bc-436f-4365-9b47-c76d90088f13","resolution":{"observed_at":"2026-08-07T05:28:11.165754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":"2310.12558","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models help humans verify truthfulness–except when they are convincingly wrong","venue":null,"work_id":"15e9e1f1-6136-4179-95a1-00077be90b8d","year":2023},"citing_paper":{"arxiv_id":"2509.08010","last_updated":"2026-05-20T11:59:51Z","snapshot_observed_at":"2026-08-15T08:10:51.326308Z","submitted_at":"2025-09-08T16:15:07Z","title":"Measuring and mitigating overreliance to build human-compatible AI","version":2},"reference_index":109,"source":"pdf_text","source_observed_at":"2026-05-21T22:37:37.267715Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2509.08010"},"observation_digest":"sha256:2399d90d6547977976aaddb000fff7069088a683e631e0c426edcb2cbcdd0df1","observation_id":"bebfc0f7-16b3-47bd-b55b-aae7bfb2e248","resolution":{"observed_at":"2026-05-21T22:40:43.444917Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":"2310.12558","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models help humans verify truthfulness–except when they are convincingly wrong","venue":null,"work_id":"15e9e1f1-6136-4179-95a1-00077be90b8d","year":2023},"citing_paper":{"arxiv_id":"2510.11954","last_updated":"2026-05-07T18:05:58Z","snapshot_observed_at":"2026-08-16T01:28:56.183106Z","submitted_at":"2025-10-13T21:28:52Z","title":"VizCopilot: Fostering Appropriate Reliance on Enterprise Chatbots with Context Visualization","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-18T07:08:14.700656Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2510.11954"},"observation_digest":"sha256:3dead94fae791efef66e5a885fd7708f4a2986b793d69a1503df5b9cd3314617","observation_id":"e014aa36-9a6b-455b-bd2c-c02696c80c6c","resolution":{"observed_at":"2026-05-18T07:11:04.081503Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-08-04T07:21:22.538224Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.26518","last_updated":"2026-06-25T13:34:02Z","snapshot_observed_at":"2026-08-10T01:21:56.171636Z","submitted_at":"2025-10-30T14:11:52Z","title":"Human-AI Complementarity: A Goal for Amplified Oversight","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-04T07:21:22.538224Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2510.26518"},"observation_digest":"sha256:7daa3caf8a7d9b77427a9345a224c20b45c0a712a5a8388a534913db515ce7c9","observation_id":"cb50a5f2-b020-4e1f-916d-52e06b00287f","resolution":{"observed_at":"2026-08-04T07:21:22.538224Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","version":2},"cited_work":{"arxiv_id":"2310.12558","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.12558","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models help humans verify truthfulness–except when they are convincingly wrong","venue":null,"work_id":"15e9e1f1-6136-4179-95a1-00077be90b8d","year":2023},"citing_paper":{"arxiv_id":"2604.20131","last_updated":"2026-04-22T02:58:51Z","snapshot_observed_at":"2026-08-14T00:03:49.600643Z","submitted_at":"2026-04-22T02:58:51Z","title":"Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives","version":1},"reference_index":149,"source":"arxiv_source","source_observed_at":"2026-05-10T01:00:41.543394Z"},"links":{"cited_paper":"/paper/2310.12558","citing_paper":"/paper/2604.20131"},"observation_digest":"sha256:53887aa1364275c4ef285942c35aafa5fae9ef3fec1fbdd87d25bad956ae9f02","observation_id":"e8af95be-2c17-431e-8e25-b187e5d37fbc","resolution":{"observed_at":"2026-05-10T01:04:50.349259Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.12558/citation-record","integrity":"/paper/2310.12558/integrity","json":"/paper/2310.12558/citation-record.json","paper":"/paper/2310.12558"},"outbound":[],"paper":{"arxiv_id":"2310.12558","last_updated":"2024-04-01T21:55:06Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-18T00:47:44.502507Z","submitted_at":"2023-10-19T08:09:58Z","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2310.12558."}