{"as_of":"2026-08-06T00:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1caef6045f277548ed143af5a0716ecb12af70aae8b5025b09fd3b838bb2dff6","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":"2026-08-05T06:32:48.257954+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":"2026-08-01T09:35:38.585115Z","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":"2026-06-29T18:43:51.205521Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.09747","last_updated":"2024-03-14T00:35:39Z","snapshot_observed_at":"2026-07-06T17:44:49.990624Z","submitted_at":"2024-03-14T00:35:39Z","title":"Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors","version":1},"cited_work":{"arxiv_id":"2403.09747","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.09747","snapshot_observed_at":"2026-06-29T18:43:51.205521Z","title":"Re-search for the truth: Multi-round retrieval-augmented large language models are strong fake news detectors","venue":null,"work_id":"86bcbfd3-304f-414b-99fc-7eea78271c22","year":2024},"citing_paper":{"arxiv_id":"2501.00309","last_updated":"2025-01-08T05:16:25Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-31T06:59:35Z","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","version":2},"reference_index":226,"source":"pdf_text","source_observed_at":"2026-05-18T04:33:39.076517Z"},"links":{"cited_paper":"/paper/2403.09747","citing_paper":"/paper/2501.00309"},"observation_digest":"sha256:af9041eb1a9f0a5aaf5fa41329811d786f114dcf697307288c684e77ac31a32b","observation_id":"e8a9775b-45e3-476b-b801-f0d5c67aafb9","resolution":{"observed_at":"2026-05-18T04:33:39.541877Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09747","last_updated":"2024-03-14T00:35:39Z","snapshot_observed_at":"2026-07-06T17:44:49.990624Z","submitted_at":"2024-03-14T00:35:39Z","title":"Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors","version":1},"cited_work":{"arxiv_id":"2403.09747","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.09747","snapshot_observed_at":"2026-06-29T18:43:51.205521Z","title":"Re-search for the truth: Multi-round retrieval-augmented large language models are strong fake news detectors","venue":null,"work_id":"86bcbfd3-304f-414b-99fc-7eea78271c22","year":2024},"citing_paper":{"arxiv_id":"2604.06687","last_updated":"2026-06-30T15:09:10Z","snapshot_observed_at":"2026-07-13T08:55:54.044324Z","submitted_at":"2026-04-08T05:03:34Z","title":"RASR: Retrieval-Augmented Semantic Reasoning for Fake News Video Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T17:57:11.383278Z"},"links":{"cited_paper":"/paper/2403.09747","citing_paper":"/paper/2604.06687"},"observation_digest":"sha256:df15773bb8aa714341258bf92a9c930cedccd381ce728491269f29ed65e0da0d","observation_id":"170f5438-e686-4402-98a1-335ec107599e","resolution":{"observed_at":"2026-05-11T05:46:12.729391Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09747","last_updated":"2024-03-14T00:35:39Z","snapshot_observed_at":"2026-07-06T17:44:49.990624Z","submitted_at":"2024-03-14T00:35:39Z","title":"Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors","version":1},"cited_work":{"arxiv_id":"2403.09747","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.09747","snapshot_observed_at":"2026-06-29T18:43:51.205521Z","title":"Re-search for the truth: Multi-round retrieval-augmented large language models are strong fake news detectors","venue":null,"work_id":"86bcbfd3-304f-414b-99fc-7eea78271c22","year":2024},"citing_paper":{"arxiv_id":"2606.27736","last_updated":"2026-06-26T05:35:27Z","snapshot_observed_at":"2026-08-02T10:42:22.872667Z","submitted_at":"2026-06-26T05:35:27Z","title":"ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-29T05:03:26.118083Z"},"links":{"cited_paper":"/paper/2403.09747","citing_paper":"/paper/2606.27736"},"observation_digest":"sha256:f8e40e6e2ec70c6a2b62a22aad17dddc65b5a6a6c5a731aacb2400570d883ffc","observation_id":"a4668af7-36aa-498c-b2ac-f0d513434845","resolution":{"observed_at":"2026-06-29T18:43:51.206982Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09747","last_updated":"2024-03-14T00:35:39Z","snapshot_observed_at":"2026-07-06T17:44:49.990624Z","submitted_at":"2024-03-14T00:35:39Z","title":"Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.09747","snapshot_observed_at":"2026-08-01T09:35:38.585115Z","title":"Re-search for the truth: Multi-round retrieval-augmented large language models are strong fake news detectors,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20730","last_updated":"2026-07-22T21:04:51Z","snapshot_observed_at":"2026-08-01T09:35:36.810972Z","submitted_at":"2026-07-22T21:04:51Z","title":"GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T09:35:38.585115Z"},"links":{"cited_paper":"/paper/2403.09747","citing_paper":"/paper/2607.20730"},"observation_digest":"sha256:e8cd5fdc538ca5edecde51d89cb8306b907169ccc762c9cb02cedf775db33615","observation_id":"523a5b80-0891-4734-b754-e21a602ed557","resolution":{"observed_at":"2026-08-01T09:35:38.585115Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2403.09747/citation-record","integrity":"/paper/2403.09747/integrity","json":"/paper/2403.09747/citation-record.json","paper":"/paper/2403.09747"},"outbound":[],"paper":{"arxiv_id":"2403.09747","last_updated":"2024-03-14T00:35:39Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:44:49.990624Z","submitted_at":"2024-03-14T00:35:39Z","title":"Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2403.09747."}