{"as_of":"2026-08-17T02:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:73ef476fa55839ca622254de635ba0e42768313194d026f82d109a4608358de0","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T00:55:27.940835Z","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":"2026-06-29T12:43:25.862605Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2509.22510","last_updated":"2026-05-15T12:53:06Z","snapshot_observed_at":"2026-08-14T16:32:52.758855Z","submitted_at":"2025-09-26T15:52:21Z","title":"We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-21T22:11:20.651761Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2509.22510"},"observation_digest":"sha256:f4caf3cc936de7d7e9f8995a8b7a045bd5cf2ee1383b6058eb2bdca2bde1471d","observation_id":"29372637-7bf9-41af-ba72-2f5882d249ac","resolution":{"observed_at":"2026-05-21T22:14:23.515618Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2510.16888","last_updated":"2025-11-04T13:15:36Z","snapshot_observed_at":"2026-08-16T11:51:43.064429Z","submitted_at":"2025-10-19T15:38:06Z","title":"Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-21T18:01:19.748677Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2510.16888"},"observation_digest":"sha256:fdb9442c27a95271a2867a752af3cec62e311cda0e683bce10d21fae99d48f1a","observation_id":"b2875207-9bb4-4b76-886a-dee3062f08f0","resolution":{"observed_at":"2026-05-21T18:01:19.783692Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2510.22977","last_updated":"2026-04-17T17:15:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-10-27T03:58:29Z","title":"The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-18T04:09:50.183494Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2510.22977"},"observation_digest":"sha256:d38f4a1d1fe0479e3a217f4ca86293f86d174137b72dc32914f0e9616f763d12","observation_id":"29a96d65-8728-4d35-83c8-c1ed1f269ee7","resolution":{"observed_at":"2026-05-18T04:10:51.361483Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2603.27771","last_updated":"2026-04-04T07:45:49Z","snapshot_observed_at":"2026-08-13T04:50:32.513154Z","submitted_at":"2026-03-29T17:10:28Z","title":"Emergent Social Intelligence Risks in Generative Multi-Agent Systems","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-14T21:45:04.625084Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2603.27771"},"observation_digest":"sha256:03b98a46f2c5a86bd96d5b52740d91b5ca7bb5217419f10fca3d35397eb44086","observation_id":"655adcfc-c0d0-4953-a244-ff9826036ecc","resolution":{"observed_at":"2026-05-14T21:48:00.866309Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2604.07655","last_updated":"2026-04-08T23:47:29Z","snapshot_observed_at":"2026-08-02T09:41:13.361711Z","submitted_at":"2026-04-08T23:47:29Z","title":"Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T17:27:13.339411Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2604.07655"},"observation_digest":"sha256:1adca623b64b46e7257ec0cfa0645861a5609a32312983997646ef6752fe2b5e","observation_id":"a5ec63fd-f489-446c-8a1f-ac74ed51c673","resolution":{"observed_at":"2026-05-11T06:46:39.768346Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":"2406.00380","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-06-29T12:43:25.862605Z","title":"Honestllm: Toward an honest and helpful large language model","venue":null,"work_id":"2e214bf7-b868-4de0-b1c8-a9ae06e0407e","year":2024},"citing_paper":{"arxiv_id":"2605.28070","last_updated":"2026-05-27T07:28:25Z","snapshot_observed_at":"2026-08-03T11:47:22.689668Z","submitted_at":"2026-05-27T07:28:25Z","title":"Bridging the Detection-to-Abstention Gap in Reasoning Models under Insufficient Information","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-29T12:37:16.138816Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2605.28070"},"observation_digest":"sha256:7a2c1bc33a48ed5686171b7d0a415703b2e3b55c48e858a65581785dc0c8fc93","observation_id":"a893ce94-1f76-4e3c-bcf5-54152b6efecd","resolution":{"observed_at":"2026-06-29T12:43:25.864138Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.00380","snapshot_observed_at":"2026-08-03T00:55:27.940835Z","title":"arXiv preprint arXiv:2406.00380 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.28636","last_updated":"2026-05-19T13:56:13Z","snapshot_observed_at":"2026-08-17T01:28:35.393539Z","submitted_at":"2026-05-19T13:56:13Z","title":"Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges","version":1},"reference_index":102,"source":"arxiv_source","source_observed_at":"2026-08-03T00:55:27.940835Z"},"links":{"cited_paper":"/paper/2406.00380","citing_paper":"/paper/2607.28636"},"observation_digest":"sha256:f3c5b727ffe5e1702a14a76b9aa3d71083dd3b0fafaf18f782d33f8179200e2e","observation_id":"16d09413-589f-41e7-b92f-5f73b0eabaa8","resolution":{"observed_at":"2026-08-03T00:55:27.940835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.00380/citation-record","integrity":"/paper/2406.00380/integrity","json":"/paper/2406.00380/citation-record.json","paper":"/paper/2406.00380"},"outbound":[],"paper":{"arxiv_id":"2406.00380","last_updated":"2024-12-11T11:52:58Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T13:47:11.136915Z","submitted_at":"2024-06-01T09:36:16Z","title":"HonestLLM: Toward an Honest and Helpful Large Language Model"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.00380."}