{"as_of":"2026-08-22T20:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c943a1f5756dd66e168520684f0cf10e4ddc6274168d16b01bf72323a420a9e","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:31:36.747097Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-12T11:31:36.747097Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18659","last_updated":"2025-07-31T07:54:00Z","snapshot_observed_at":"2026-08-17T13:45:25.648791Z","submitted_at":"2024-11-27T09:43:09Z","title":"DHCP: Detecting Hallucinations by Cross-modal Attention Pattern in Large Vision-Language Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T11:31:36.747097Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2411.18659"},"observation_digest":"sha256:d39c03e8e5c8c670c0845751ae258b7c39913d038ca97d45d028aa2f0ad306bf","observation_id":"a438c9cd-e55d-426b-b866-61b0be98ada4","resolution":{"observed_at":"2026-08-12T11:31:36.747097Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-11T20:37:54.583028Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.05563","last_updated":"2025-07-01T22:08:39Z","snapshot_observed_at":"2026-08-16T14:41:18.143042Z","submitted_at":"2024-12-07T06:56:01Z","title":"A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T20:37:54.583028Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2412.05563"},"observation_digest":"sha256:e7ff88986d39b08c1f2ee6fa21b252149fdbddd2fe5159ba817857730e873807","observation_id":"ae5b83a1-0ee7-4110-b897-af04610e8818","resolution":{"observed_at":"2026-08-11T20:37:54.583028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-11T19:01:49.591848Z","title":"Arteaga, Thomas B","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.07282","last_updated":"2025-05-24T10:21:48Z","snapshot_observed_at":"2026-08-16T17:50:33.748845Z","submitted_at":"2024-12-10T08:12:22Z","title":"HARP: Hesitation-Aware Reframing in Transformer Inference Pass","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-11T19:01:49.591848Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2412.07282"},"observation_digest":"sha256:a9ba92c1c2837e275ce560ba7b5043116db29e6654f369d40b2656de116022f5","observation_id":"ab75da89-c469-4dfa-88fe-bf76c2487547","resolution":{"observed_at":"2026-08-11T19:01:49.591848Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-07T14:06:31.972141Z","title":"Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.20047","last_updated":"2025-05-26T14:34:04Z","snapshot_observed_at":"2026-08-21T05:23:29.889021Z","submitted_at":"2025-05-26T14:34:04Z","title":"Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:06:31.972141Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2505.20047"},"observation_digest":"sha256:cbf489bb9786f5111a0f3a39f61f54fb352d8ef2b6a54342118b67c9270c09e4","observation_id":"7ca760b9-ce92-4066-84e9-27a2b8c60474","resolution":{"observed_at":"2026-08-07T14:06:31.972141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-05T23:01:43.524922Z","title":"Hallucination detection in llms: Fast and memory-efficient finetuned models.arXiv:2409.02976, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06014","last_updated":"2025-08-08T05:01:17Z","snapshot_observed_at":"2026-08-15T18:00:58.571548Z","submitted_at":"2025-08-08T05:01:17Z","title":"ExploreGS: Explorable 3D Scene Reconstruction with Virtual Camera Samplings and Diffusion Priors","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T23:01:43.524922Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2508.06014"},"observation_digest":"sha256:7000bb42a42b1e395c4c3f90fd315c87e47650379134d1375db161fefb6c26fd","observation_id":"1b415eb8-5216-448b-8c77-d5f9725338dd","resolution":{"observed_at":"2026-08-05T23:01:43.524922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models","version":2},"cited_work":{"arxiv_id":"2409.02976","doi":"10.48550/arxiv.2409.02976","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.02976","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"and Schön, Thomas B","venue":"arXiv (Cornell University)","work_id":"1bd19d6e-a1f6-4707-b3bb-d41cd7abe1f9","year":null},"citing_paper":{"arxiv_id":"2605.12813","last_updated":"2026-05-31T17:51:51Z","snapshot_observed_at":"2026-08-20T19:02:09.543322Z","submitted_at":"2026-05-12T23:13:50Z","title":"REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-05-14T20:13:10.814899Z"},"links":{"cited_paper":"/paper/2409.02976","citing_paper":"/paper/2605.12813"},"observation_digest":"sha256:e725affacf0f69fe48a5360e92cf7f28af64dd5908b1c365ddb132383ec6de08","observation_id":"7fb53fd2-383c-409b-af5c-c1b78695311c","resolution":{"observed_at":"2026-05-14T20:17:56.384639Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.02976/citation-record","integrity":"/paper/2409.02976/integrity","json":"/paper/2409.02976/citation-record.json","paper":"/paper/2409.02976"},"outbound":[],"paper":{"arxiv_id":"2409.02976","last_updated":"2024-12-06T12:39:00Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-21T22:38:16.278590Z","submitted_at":"2024-09-04T13:59:38Z","title":"Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models"},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.02976."}