{"as_of":"2026-08-09T10:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:09ad07b4a1d5bd35be11c0a99618e5d3ffffecd06d74b95b9507c99995f740e6","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":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":23,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:49:26.536527Z","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":"2026-07-03T20:18:56.453951Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-06T23:49:26.536527Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.16064","last_updated":"2025-06-19T06:42:35Z","snapshot_observed_at":"2026-08-08T11:18:17.446928Z","submitted_at":"2025-06-19T06:42:35Z","title":"Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:49:26.536527Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2506.16064"},"observation_digest":"sha256:b612e69538056384ab111ed5e7fdd399d8ab75940ab69e9080b50fd0b0d398d0","observation_id":"3995264e-ac85-43b4-8c73-c5a42d2b2e2f","resolution":{"observed_at":"2026-08-06T23:49:26.536527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-04T18:01:56.731469Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.10297","last_updated":"2025-09-12T14:37:57Z","snapshot_observed_at":"2026-08-04T18:01:46.972785Z","submitted_at":"2025-09-12T14:37:57Z","title":"The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-04T18:01:56.731469Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2509.10297"},"observation_digest":"sha256:24aff7af92bf0a8397fcbdf24dcc1c8bc3cbc427bbd4fb5e95664e5166430713","observation_id":"e27fd484-d4f4-46ad-b76d-9aaa5499059c","resolution":{"observed_at":"2026-08-04T18:01:56.731469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-04T06:57:04.937599Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.00215","last_updated":"2026-07-29T19:12:44Z","snapshot_observed_at":"2026-08-04T06:57:01.104328Z","submitted_at":"2025-10-31T19:22:54Z","title":"DocPrism: Multi-lingual Detection of Incorrectness Inconsistencies between Code and Documentation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T06:57:04.937599Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2511.00215"},"observation_digest":"sha256:574bfdc99ea3c6972d22b0f99077fa91d8ae1343f2355621da5e157f1e9e6e1c","observation_id":"e1d618bb-c286-4303-993a-10377c2906f5","resolution":{"observed_at":"2026-08-04T06:57:04.937599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2601.10467","last_updated":"2026-05-05T15:17:14Z","snapshot_observed_at":"2026-08-02T01:41:38.660629Z","submitted_at":"2026-01-15T14:51:50Z","title":"User Detection and Response Patterns of Sycophantic Behavior in Conversational AI","version":4},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-16T14:03:49.595868Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2601.10467"},"observation_digest":"sha256:04a3fb4e6e07b7d08fd87a7d6528844f5cd837b40090b649901ab76ffc2264d1","observation_id":"3904b4c0-9503-45f2-b6ce-2008d5c0d6dd","resolution":{"observed_at":"2026-05-16T14:07:58.802378Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2604.05279","last_updated":"2026-04-07T00:28:17Z","snapshot_observed_at":"2026-08-08T04:17:53.842643Z","submitted_at":"2026-04-07T00:28:17Z","title":"Pressure, What Pressure? Sycophancy Disentanglement in Language Models via Reward Decomposition","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T20:10:56.036361Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2604.05279"},"observation_digest":"sha256:cc257cfff6d84056d1665782216c9a6a8cf7c26ac9fe2956addfc94a56e7f6fd","observation_id":"d271fb54-e601-4f70-8a09-c6a2e1970ca4","resolution":{"observed_at":"2026-05-10T22:10:49.245720Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2604.13803","last_updated":"2026-04-15T12:38:51Z","snapshot_observed_at":"2026-07-06T23:01:41.643335Z","submitted_at":"2026-04-15T12:38:51Z","title":"Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-10T13:09:35.407790Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2604.13803"},"observation_digest":"sha256:4b49069181ea1ff3759184eb50e069a6c512492902a222b01f5f20ece20338de","observation_id":"8c8deb84-aebb-4bd6-b153-2847500a4c56","resolution":{"observed_at":"2026-05-10T13:10:26.242772Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2604.20652","last_updated":"2026-04-23T15:40:50Z","snapshot_observed_at":"2026-07-06T23:07:14.243878Z","submitted_at":"2026-04-22T15:03:37Z","title":"Large Language Models Outperform Humans in Fraud Detection and Resistance to Motivated Investor Pressure","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-09T23:40:00.572491Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2604.20652"},"observation_digest":"sha256:3f3c241c78e58462d163dd548aa147d12f68beef17d639e1e293e2b4a8960be3","observation_id":"f94bd42d-84c2-48db-a4cf-2cf6c0abc78a","resolution":{"observed_at":"2026-05-11T14:06:02.516341Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2605.05403","last_updated":"2026-05-06T19:36:41Z","snapshot_observed_at":"2026-08-02T10:40:01.385625Z","submitted_at":"2026-05-06T19:36:41Z","title":"When Helpfulness Becomes Sycophancy: Sycophancy is a Boundary Failure Between Social Alignment and Epistemic Integrity in Large Language Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-08T17:13:19.119896Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2605.05403"},"observation_digest":"sha256:2091411fb992e9688134e09e9be4600beab3d1b16705ec1d6de9c62656a99523","observation_id":"869f721e-3266-4a5f-a042-bec81792d581","resolution":{"observed_at":"2026-05-11T17:46:08.507033Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2605.05957","last_updated":"2026-05-08T12:09:34Z","snapshot_observed_at":"2026-07-06T23:18:31.432422Z","submitted_at":"2026-05-07T10:04:39Z","title":"Knowing but Not Correcting: Routine Task Requests Suppress Factual Correction in LLMs","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-11T01:50:02.810240Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2605.05957"},"observation_digest":"sha256:acca673c95e6bd74cb4cb08a63a642bef7d023d8967befb7d66fe284c18f4883","observation_id":"69f4122b-2b2a-4fb5-b4a7-79873b9d7395","resolution":{"observed_at":"2026-05-11T01:50:51.130101Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2605.06476","last_updated":"2026-05-07T16:01:48Z","snapshot_observed_at":"2026-08-01T20:48:22.419665Z","submitted_at":"2026-05-07T16:01:48Z","title":"Towards Emotion Consistency Analysis of Large Language Models in Emotional Conversational Contexts","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T10:17:35.694775Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2605.06476"},"observation_digest":"sha256:15beff4acaf873599ccfd3aaf5cfadb147e7f4578ec8d98b0d105e42eb147a17","observation_id":"53744903-5b57-4d71-ba83-d3339f4abe1c","resolution":{"observed_at":"2026-05-11T20:06:12.878041Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-12T23:30:07.574017Z","title":"and Pucci, G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2605.27382","last_updated":"2026-05-28T02:39:08Z","snapshot_observed_at":"2026-08-03T01:58:37.654742Z","submitted_at":"2026-04-10T08:04:41Z","title":"The Alignment Floor: How Persona Customization Breaks Safety in Weakly-Aligned LLMs","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-12T23:30:07.574017Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2605.27382"},"observation_digest":"sha256:65af5d814aadac731502c0dca5dfca3c270109ac762b7d580dfba0ef5ced79f6","observation_id":"9990a91c-304e-450b-9aa2-d8fdda7881fc","resolution":{"observed_at":"2026-07-12T23:30:07.574017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.02444","last_updated":"2026-06-01T16:14:18Z","snapshot_observed_at":"2026-07-06T23:42:49.173711Z","submitted_at":"2026-06-01T16:14:18Z","title":"Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedback","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-06-28T14:09:37.523725Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.02444"},"observation_digest":"sha256:e27d6ae2c94112169b86a6b7309f2e62fea4dc15f9b877119289c05f33f3b6e4","observation_id":"de066f7f-642b-4d6e-816b-38c85096a8b8","resolution":{"observed_at":"2026-07-01T23:36:23.477673Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.06306","last_updated":"2026-06-04T15:44:31Z","snapshot_observed_at":"2026-08-07T19:25:23.088606Z","submitted_at":"2026-06-04T15:44:31Z","title":"Decomposing Factual Sycophancy in Language Models: How Size and Instruction Tuning Shape Robustness","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-06-28T01:38:09.762751Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.06306"},"observation_digest":"sha256:7017cf9c49ee0a74f9f52929558cd711ffc31a56c43cf8935057c415d69de147","observation_id":"7f183e93-0fbb-412e-bf2f-c04d2fc5529c","resolution":{"observed_at":"2026-07-02T13:06:58.887637Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.10158","last_updated":"2026-06-08T20:36:57Z","snapshot_observed_at":"2026-07-06T23:49:22.753911Z","submitted_at":"2026-06-08T20:36:57Z","title":"\"Where is this coming from?\" Uncovering Trustworthiness Ideals in AI-powered Peripartum Information Seeking","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-06-27T14:30:16.124527Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.10158"},"observation_digest":"sha256:d61e48a67b57190958c42f763f178cb9e796abeeb5221de1231a6021dfaa3e07","observation_id":"b4da3eea-b8e8-40ee-8339-a6c0cdcc6a47","resolution":{"observed_at":"2026-07-03T03:47:36.194441Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.10949","last_updated":"2026-06-09T14:53:32Z","snapshot_observed_at":"2026-08-02T23:45:38.545352Z","submitted_at":"2026-06-09T14:53:32Z","title":"Recalling Too Well: Sycophancy Evaluation and Mitigation in Memory-Augmented Models","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-06-27T12:59:17.696736Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.10949"},"observation_digest":"sha256:976b62f018e54b6d2650a2b04931dbcea23962632a54664cef66413409367214","observation_id":"d842a853-71d1-419c-9b69-104c69403db6","resolution":{"observed_at":"2026-07-03T05:57:41.801669Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.13220","last_updated":"2026-06-11T11:37:07Z","snapshot_observed_at":"2026-07-06T23:51:59.619032Z","submitted_at":"2026-06-11T11:37:07Z","title":"LLM-as-an-Investigator: Evidence-First Reasoning for Robust Interactive Problem Diagnosis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T06:58:42.823851Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.13220"},"observation_digest":"sha256:bdfe45cbc2d57aedbd9d1cbd0aeafe9dd7cd836992de7b0fece817ea10bbd981","observation_id":"925eba21-ff07-4b3c-8e2b-eef7d975dd6c","resolution":{"observed_at":"2026-07-03T14:38:29.235459Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2606.18060","last_updated":"2026-06-16T15:37:02Z","snapshot_observed_at":"2026-08-03T13:40:03.995669Z","submitted_at":"2026-06-16T15:37:02Z","title":"PseudoBench: Measuring How Agentic Auto-Research Fuels Pseudoscience","version":1},"reference_index":143,"source":"arxiv_source","source_observed_at":"2026-06-27T01:29:12.725865Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2606.18060"},"observation_digest":"sha256:384ce9c9f16c124511c01af5af599cb54adca1fd6e263e6a6d36574dc66d88d4","observation_id":"9e8dae72-4a7c-4688-84bd-e0e8bb71081c","resolution":{"observed_at":"2026-07-03T20:18:56.455747Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2607.01071","last_updated":"2026-07-02T15:40:30Z","snapshot_observed_at":"2026-07-07T00:06:39.908636Z","submitted_at":"2026-07-01T15:30:33Z","title":"MemSyco-Bench: Benchmarking Sycophancy in Agent Memory","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-02T06:29:32.975530Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2607.01071"},"observation_digest":"sha256:da0d580cbfaa4834e932e98b66669cf1ed62baf50c2df3e98c0d8bc272adb44f","observation_id":"5435de74-57e7-4e18-8fba-edb3b5469f5e","resolution":{"observed_at":"2026-07-02T06:36:43.291737Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2607.01071","last_updated":"2026-07-02T15:40:30Z","snapshot_observed_at":"2026-07-07T00:06:39.908636Z","submitted_at":"2026-07-01T15:30:33Z","title":"MemSyco-Bench: Benchmarking Sycophancy in Agent Memory","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-03T18:50:02.455542Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2607.01071"},"observation_digest":"sha256:74ed67c5103cd5369fdea8a68f90b571c8e6afe23cf04d5b63b2fdf9c859c4b8","observation_id":"25b1d6b5-94ef-4b4c-b265-266ad7ad385c","resolution":{"observed_at":"2026-07-03T18:58:50.749581Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":"2311.09410","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-07-03T20:18:56.453951Z","title":"When large language models contradict humans? large language models’ sycophantic behaviour","venue":null,"work_id":"c21d1629-4e90-4a38-b5d7-4a379bcd969a","year":2023},"citing_paper":{"arxiv_id":"2607.01951","last_updated":"2026-07-02T09:40:52Z","snapshot_observed_at":"2026-08-07T21:49:49.866198Z","submitted_at":"2026-07-02T09:40:52Z","title":"Robust for the Wrong Reasons: The Representational Geometry of LLM Robustness to Science Skepticism","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-03T03:26:40.531292Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2607.01951"},"observation_digest":"sha256:c17ad48335a21eb078e4dd7881b57ffbb40c8aacce6ef8b9c95a95da6c69cd3d","observation_id":"bed63401-c31b-48a6-b8f1-5b7995f5eb48","resolution":{"observed_at":"2026-07-03T03:27:34.713687Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-01T22:47:07.223036Z","title":"Leonardo Ranaldi and Giulia Pucci","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18304","last_updated":"2026-07-17T05:25:48Z","snapshot_observed_at":"2026-08-06T15:54:26.090836Z","submitted_at":"2026-07-17T05:25:48Z","title":"TD-DPO: Difference-Aware Preference Optimization for Mitigating Sycophancy in Clinical Autism Intervention Dialogue","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-01T22:47:07.223036Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2607.18304"},"observation_digest":"sha256:9636661f6f4fa58930bf83df2f5cd91a251b0b5ed38be85ec71a94a0d11d2560","observation_id":"e1b91609-6f5f-498c-aa06-797fe1a763e7","resolution":{"observed_at":"2026-08-01T22:47:07.223036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-01T08:36:26.253602Z","title":"arXiv preprint arXiv:2311.09410 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21090","last_updated":"2026-07-23T09:20:38Z","snapshot_observed_at":"2026-08-06T22:04:57.750051Z","submitted_at":"2026-07-23T09:20:38Z","title":"Training Large Language Models for Self-Explanation Faithfulness","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-01T08:36:26.253602Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2607.21090"},"observation_digest":"sha256:22d750f8ac1bfa7e60cd5ec5dd8054144049703b4bf1096eb552e02e0a245031","observation_id":"62d19569-5f5b-441f-a69f-c208a209f214","resolution":{"observed_at":"2026-08-01T08:36:26.253602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09410","snapshot_observed_at":"2026-08-06T23:42:20.275733Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.04463","last_updated":"2026-08-05T05:38:34Z","snapshot_observed_at":"2026-08-08T23:11:43.601183Z","submitted_at":"2026-08-05T05:38:34Z","title":"The Evaluator Is Part of the Experiment: Measuring Open-Ended LLM Conformity","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T23:42:20.275733Z"},"links":{"cited_paper":"/paper/2311.09410","citing_paper":"/paper/2608.04463"},"observation_digest":"sha256:3a449f7f5aca20308deea5f2600d2cc936aa62c7baabc6b1f3f97c0bc534173f","observation_id":"a96f5d90-1c8a-4ce4-b923-6715104a54c6","resolution":{"observed_at":"2026-08-06T23:42:20.275733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2311.09410/citation-record","integrity":"/paper/2311.09410/integrity","json":"/paper/2311.09410/citation-record.json","paper":"/paper/2311.09410"},"outbound":[],"paper":{"arxiv_id":"2311.09410","last_updated":"2025-06-24T19:59:56Z","latest_version":4,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T16:48:16.671370Z","submitted_at":"2023-11-15T22:18:33Z","title":"When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2311.09410."}