{"as_of":"2026-08-08T22:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:37a19a2aae36e2c81f6a7fda14962be83abeec1c389cc911fb97843a59b212d2","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:36:31.980599Z","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":"2026-07-03T02:07:34.251784Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-08-07T14:09:51.291020Z","title":"arXiv preprint arXiv:2504.10430","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19806","last_updated":"2025-05-26T10:40:52Z","snapshot_observed_at":"2026-08-08T21:21:56.023033Z","submitted_at":"2025-05-26T10:40:52Z","title":"Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Risks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:51.291020Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2505.19806"},"observation_digest":"sha256:511b94f5421e006b4e5fa4482d6ce75ef34e97b008ef7dcaaeaf4b0e1ed121ee","observation_id":"b59a016d-ccb6-4a09-965b-0be8dafbcdf8","resolution":{"observed_at":"2026-08-07T14:09:51.291020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-08-04T20:03:40.360991Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08912","last_updated":"2025-09-10T18:16:46Z","snapshot_observed_at":"2026-08-07T20:13:30.269872Z","submitted_at":"2025-09-10T18:16:46Z","title":"Towards Trustworthy AI: Characterizing User-Reported Risks across LLMs \"In the Wild\"","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-04T20:03:40.360991Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2509.08912"},"observation_digest":"sha256:3edbb7f8e4cd5b8418c6f07884990d2dd869e06a042e2450712fd718aa039b7d","observation_id":"869f3e44-62da-4319-96d2-87cbed42d3a5","resolution":{"observed_at":"2026-08-04T20:03:40.360991Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.10430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-03T02:07:34.251784Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","venue":null,"work_id":"c9d2ab09-aaca-4781-9412-fba2ca9a3ca6","year":2025},"citing_paper":{"arxiv_id":"2510.12826","last_updated":"2026-04-25T22:54:37Z","snapshot_observed_at":"2026-08-05T08:30:16.216064Z","submitted_at":"2025-10-11T04:42:29Z","title":"Scheming Ability in LLM-to-LLM Strategic Interactions","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-18T07:50:30.597108Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2510.12826"},"observation_digest":"sha256:ea7d89400a3d346c4f104d16d470e36b38fe93a19cf48ac18443480b51fdf619","observation_id":"6427c47e-aff5-45fc-830a-4a77710469ba","resolution":{"observed_at":"2026-05-18T07:51:03.814941Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"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":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-08-03T11:35:39.785391Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.05751","last_updated":"2026-06-05T07:06:47Z","snapshot_observed_at":"2026-08-04T17:00:12.286204Z","submitted_at":"2026-01-09T12:07:38Z","title":"Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-03T11:35:39.785391Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2601.05751"},"observation_digest":"sha256:60f054691ad8d4f4f0b84479b411ed70fa36a4a93bc9dc1ec2d48b27d4da0afa","observation_id":"6c33aff3-e72f-4c0e-9a3c-8efd8778a8a7","resolution":{"observed_at":"2026-08-03T11:35:39.785391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-08-02T16:48:10.722428Z","title":"Stephanie Lin, Jacob Hilton, and Owain Evans","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2604.04788","last_updated":"2026-07-20T00:32:35Z","snapshot_observed_at":"2026-08-02T16:48:09.987320Z","submitted_at":"2026-04-06T15:57:47Z","title":"From Sycophancy to Deception: A Unified Taxonomy for LLM Spontaneous Misalignment","version":2},"reference_index":397,"source":"pdf_text","source_observed_at":"2026-08-02T16:48:10.722428Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2604.04788"},"observation_digest":"sha256:97ab08316e1f2a7f7fa9af01df9c95de8e0d0bd80834b4fc2fa20500bf737a5d","observation_id":"718b041d-4db6-490d-9e33-22d5dda4e059","resolution":{"observed_at":"2026-08-02T16:48:10.722428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.10430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-03T02:07:34.251784Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","venue":null,"work_id":"c9d2ab09-aaca-4781-9412-fba2ca9a3ca6","year":2025},"citing_paper":{"arxiv_id":"2605.12772","last_updated":"2026-05-12T21:34:33Z","snapshot_observed_at":"2026-08-07T01:04:45.549282Z","submitted_at":"2026-05-12T21:34:33Z","title":"Just Ask for a Table: A Thirty-Token User Prompt Defeats Sponsored Recommendations in Twelve LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-14T20:43:26.831414Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2605.12772"},"observation_digest":"sha256:ddd7f9a9a664c0e62cc83a25dd8b4e3005739ffe2b1a554439645906ddd5ed3c","observation_id":"22087685-1f5f-45db-821b-cb70474a1a3f","resolution":{"observed_at":"2026-05-14T20:47:59.014311Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.10430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-03T02:07:34.251784Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","venue":null,"work_id":"c9d2ab09-aaca-4781-9412-fba2ca9a3ca6","year":2025},"citing_paper":{"arxiv_id":"2606.05330","last_updated":"2026-06-03T18:17:20Z","snapshot_observed_at":"2026-08-03T19:00:51.745221Z","submitted_at":"2026-06-03T18:17:20Z","title":"A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-06-28T06:17:01.173495Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2606.05330"},"observation_digest":"sha256:23b8423ea92bc5e577d01c316cf132160ee7eb2ed0dbdaf1d2815cbba8b24e4b","observation_id":"c7b6e86c-c2b8-4932-be76-464ee6cf9776","resolution":{"observed_at":"2026-07-02T08:16:47.516636Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.10430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-03T02:07:34.251784Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","venue":null,"work_id":"c9d2ab09-aaca-4781-9412-fba2ca9a3ca6","year":2025},"citing_paper":{"arxiv_id":"2606.06099","last_updated":"2026-06-04T12:38:43Z","snapshot_observed_at":"2026-08-02T12:02:16.707363Z","submitted_at":"2026-06-04T12:38:43Z","title":"CogManip: Benchmarking Manipulative Behavior in Multi-Turn Interactions with Large Language Model","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-06-28T01:41:26.750771Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2606.06099"},"observation_digest":"sha256:86186d1b4e98d969ca8e8e19e5952b642c695bf23287c8a85757a4709ff6dc61","observation_id":"7fdc337d-fce6-4eeb-ab7a-ff720c2f1d95","resolution":{"observed_at":"2026-07-02T12:56:57.381211Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.10430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-03T02:07:34.251784Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","venue":null,"work_id":"c9d2ab09-aaca-4781-9412-fba2ca9a3ca6","year":2025},"citing_paper":{"arxiv_id":"2606.10126","last_updated":"2026-06-08T19:57:13Z","snapshot_observed_at":"2026-08-04T20:33:47.662321Z","submitted_at":"2026-06-08T19:57:13Z","title":"Pareto-Guided Teacher Alignment for Fair Personalized Text Generation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-06-27T16:06:58.653836Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2606.10126"},"observation_digest":"sha256:22e053456ef4a4ab60e1b2e4b6300e975f7543188fff23d9a9535b79fa103359","observation_id":"4ebff0a8-bde2-4f74-8f46-62ccd97543b1","resolution":{"observed_at":"2026-07-03T02:07:34.253157Z","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":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-07-31T04:54:36.088046Z","title":"Wisniewski, Jin- Hee Cho, Sang Won Lee, Ruoxi Jia, et al","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24964","last_updated":"2026-07-27T18:13:28Z","snapshot_observed_at":"2026-08-07T06:05:15.080571Z","submitted_at":"2026-07-27T18:13:28Z","title":"ALIBI: Adaptive Agentic Attacks on LLM-Based Vulnerability Detectors via Adversarial Code Comments","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-31T04:54:36.088046Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2607.24964"},"observation_digest":"sha256:d448128e2d084c38756a93447877fca1a79ba8181b36656771cc09e0ccae3400","observation_id":"7512d795-92cc-4b62-93ac-09b09473eabb","resolution":{"observed_at":"2026-07-31T04:54:36.088046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10430","snapshot_observed_at":"2026-08-07T15:36:31.980599Z","title":"arXiv:2504.10430 [cs.CL] https://arxiv.org/abs/2504","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06068","last_updated":"2026-08-06T14:12:14Z","snapshot_observed_at":"2026-08-08T22:18:45.817385Z","submitted_at":"2026-08-06T14:12:14Z","title":"Cleo: A Transparent and Controllable Chatbot for Conversational Commerce","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T15:36:31.980599Z"},"links":{"cited_paper":"/paper/2504.10430","citing_paper":"/paper/2608.06068"},"observation_digest":"sha256:8694b72d0ff542e46634fdf99d684f51abc717433c75fa3a12f675ba65fef4e2","observation_id":"8f673186-e965-4960-8056-2baa860a4b61","resolution":{"observed_at":"2026-08-07T15:36:31.980599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.10430/citation-record","integrity":"/paper/2504.10430/integrity","json":"/paper/2504.10430/citation-record.json","paper":"/paper/2504.10430"},"outbound":[],"paper":{"arxiv_id":"2504.10430","last_updated":"2025-04-14T17:20:34Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T16:05:47.962526Z","submitted_at":"2025-04-14T17:20:34Z","title":"LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language 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":"2026-08-08T06:32:00.761636+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 11 inbound Pith citation observations for arXiv:2504.10430."}