{"as_of":"2026-08-09T01:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:03a88f7e5dc1cb564c06208fe3a8f62158ca3be8214e06bc078b8a8cfd9728a5","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T13:26:28.271210Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:18:52.158408Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T15:18:54.668962Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"cited_work":{"arxiv_id":"2607.19355","doi":null,"metadata_source":"pith","pith_arxiv_id":"2607.19355","snapshot_observed_at":"2026-08-07T15:18:54.668962Z","title":"Information Discernment in Large Language Models","venue":"cs.AI","work_id":"5544d838-73ea-48cb-bb9f-2a0e6fa1417e","year":2026},"citing_paper":{"arxiv_id":"2608.06085","last_updated":"2026-08-06T14:27:46Z","snapshot_observed_at":"2026-08-09T01:12:22.935658Z","submitted_at":"2026-08-06T14:27:46Z","title":"Signal or Spurious Cue? A Randomized Audit of Survey-Country Metadata in LLM Social Inference","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-07T15:18:52.158408Z"},"links":{"cited_paper":"/paper/2607.19355","citing_paper":"/paper/2608.06085"},"observation_digest":"sha256:114e0aaef730dfaff383dd61c84d382e41b25c04e2dfca9c81dfd30ebc850110","observation_id":"1df49147-41eb-45dd-aaae-df3caa769b53","resolution":{"observed_at":"2026-08-07T15:18:54.851002Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2607.19355/citation-record","integrity":"/paper/2607.19355/integrity","json":"/paper/2607.19355/citation-record.json","paper":"/paper/2607.19355"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:23.752309Z","title":"Deep Value Benchmark: Measuring Whether Models Generalize Deep Values or Shallow Preferences","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:23.752309Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:9bb2cf5c5b1f2e679f9731b135e757188c77a39999cfb86fe9081cc7b0497354","observation_id":"47515324-bb26-42b0-a9e7-c1aff881064f","resolution":{"observed_at":"2026-08-02T13:26:23.752309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41586-023-06883-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Nature","work_id":"4b54389e-5e42-41ec-89bd-ba998ab33ff0","year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:23.846059Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:e1a20d7284aed92a2b401819a1c4705894b53627c8646e14c2ce3d0f7d478305","observation_id":"307aad14-992c-46c6-be1b-e86a704d0901","resolution":{"observed_at":"2026-08-02T13:28:58.444536Z","resolver_source":"doi","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":null,"cited_work":{"arxiv_id":null,"doi":"10.5395/rde.2024.49.e21","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Restorative Dentistry & Endodontics","work_id":"e8adb904-b122-4e10-8742-82274b93c540","year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.014387Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:c8be7eb3a667af779bb2ee31f3ef4be835dbc986023ba521fc78e55de2c62cd2","observation_id":"c656c6ae-51ab-4906-9b0f-077f83f7c141","resolution":{"observed_at":"2026-08-02T13:28:58.242023Z","resolver_source":"doi","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:24.176329Z","title":"MAIN- RAG: Multi-Agent Filtering Retrieval-Augmented Generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.176329Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:cfde352d18fd42ff6f88dd497c02354b0d1db7f8e6b62ea483d4e03b0fc37f73","observation_id":"5fb5c4aa-5620-4d6b-880b-2d9d8ce0bb39","resolution":{"observed_at":"2026-08-02T13:26:24.176329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:24.338433Z","title":"Combating misinformation in the age of LLMs: Opportunities and challenges.AI Magazine, 45(3):354–368, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.338433Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:0f1237e032ece38468605f61cf0a902d7d0e80fcbd0f3cce867dd606fcce07de","observation_id":"fcd1fb56-db51-4034-abf1-fa153ddff153","resolution":{"observed_at":"2026-08-02T13:26:24.338433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:24.506272Z","title":"A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.506272Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:7236f64910c5e8ecde144930cf68698a3cba91bcadc4f3f577ba7a5a18be4379","observation_id":"e4bc15ba-b8db-4274-9f4e-3f2686ed6db7","resolution":{"observed_at":"2026-08-02T13:26:24.506272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13805","last_updated":"2024-06-19T20:13:42Z","snapshot_observed_at":"2026-07-06T18:33:54.443005Z","submitted_at":"2024-06-19T20:13:42Z","title":"WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13805","snapshot_observed_at":"2026-08-02T13:26:24.620624Z","title":"WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.620624Z"},"links":{"cited_paper":"/paper/2406.13805","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:39a6f8cf7a27f6fd2642cdb8b816c5bc004ce35a15388c803541c65d503040bf","observation_id":"ce95dddb-3b04-46de-ab4a-3c6fa7992285","resolution":{"observed_at":"2026-08-02T13:26:24.620624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.03551","last_updated":"2017-05-13T21:12:37Z","snapshot_observed_at":"2026-08-02T11:13:42.401488Z","submitted_at":"2017-05-09T21:35:07Z","title":"TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.03551","snapshot_observed_at":"2026-08-02T13:26:24.781704Z","title":"Weld, and Luke Zettlemoyer","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.781704Z"},"links":{"cited_paper":"/paper/1705.03551","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:c9a55f26a346ecc2abe4185fdbe6bbbf524b106bbbb3b0904d4e4c3bd716e676","observation_id":"69e01775-ca02-45ce-9cd3-1e031e6e22b9","resolution":{"observed_at":"2026-08-02T13:26:24.781704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.07566","last_updated":"2021-07-15T19:00:35Z","snapshot_observed_at":"2026-07-06T11:29:34.579530Z","submitted_at":"2021-07-15T19:00:35Z","title":"Internet-Augmented Dialogue Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.07566","snapshot_observed_at":"2026-08-02T13:26:24.943776Z","title":"Internet-Augmented Dialogue Generation, July 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:24.943776Z"},"links":{"cited_paper":"/paper/2107.07566","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:f250ce6032030ab9296ec28e29056a8ccc90360569ccdf048a4e9f5dc07d673c","observation_id":"40b08fe8-fa99-4622-a8b8-f8a0b01836c3","resolution":{"observed_at":"2026-08-02T13:26:24.943776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.069574Z","title":"Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.069574Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:f8407f91f53b2a4ae0d6aa004e8e5233d5d20db345077957a827dd9daaeae038","observation_id":"08d90ece-586a-4660-8637-6c05bab94df0","resolution":{"observed_at":"2026-08-02T13:26:25.069574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.223860Z","title":"Learning Question Classifiers","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.223860Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:7d61939b4c60264d3453494a6455083e1b8a17b8413b7f8b3c78f66fd41ed948","observation_id":"e2337d4d-22aa-4d5b-af93-1fccc1501442","resolution":{"observed_at":"2026-08-02T13:26:25.223860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.00683","last_updated":"2020-09-18T00:42:25Z","snapshot_observed_at":"2026-07-06T09:17:02.233694Z","submitted_at":"2020-05-02T02:47:02Z","title":"Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.00683","snapshot_observed_at":"2026-08-02T13:26:25.258062Z","title":"Birds have four legs?! Nu- merSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Mod- els, September 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.258062Z"},"links":{"cited_paper":"/paper/2005.00683","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:f5aae73835b87c3b1c9af36eca0e8cd9091f612339d00f75e16cb350be4d5db4","observation_id":"a5986705-e5b9-4275-87f2-8a91caccc614","resolution":{"observed_at":"2026-08-02T13:26:25.258062Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.31234/osf.io/u8anb","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reducing misinformation sharing at scale using digital accuracy prompt ads, February 2024","venue":null,"work_id":"ae162038-da23-4581-b2ae-57e4c77152cf","year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.314971Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:d1f32bfe87ba069ac711f03228c7a62dff0b016bd970af8ff65a1cf25f856da3","observation_id":"8fd2142a-3120-40cd-8c52-39abbf07cc24","resolution":{"observed_at":"2026-08-02T13:28:58.018086Z","resolver_source":"doi","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.427536Z","title":"High level of correspondence across different news domain quality rating sets.PNAS Nexus, 2(9):pgad286, September 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.427536Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:8b9ae5ecfcbfab80548f81e1293eccb610f1b4db7e6f25fde660bd41e2d168c2","observation_id":"8a24220d-74e2-419d-872b-15e0fe48599d","resolution":{"observed_at":"2026-08-02T13:26:25.427536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.540904Z","title":"The Moon is Made of Marshmallows","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.540904Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:10b402e83cf08673be5a525028b40ff135ca652a7a301a7702d524fbab44b458","observation_id":"72bdb43e-a70d-47eb-a37e-f61e27e6a8fc","resolution":{"observed_at":"2026-08-02T13:26:25.540904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.617470Z","title":"General Social Survey, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.617470Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:052cf2df29bc2be57d9e2189d285fd2aae02001cd132558a379f3244d53adb6d","observation_id":"c4cd0fad-d5c3-46d9-9d29-856b695487ed","resolution":{"observed_at":"2026-08-02T13:26:25.617470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.731576Z","title":"Attacking Open- domain Question Answering by Injecting Misinformation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.731576Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:fc5074bb04f3add7f1409ca63883f201470f3f4c8c836a0bcc37dab312ac5ff0","observation_id":"46f6c7ff-eefa-42bd-87ec-734e92384a89","resolution":{"observed_at":"2026-08-02T13:26:25.731576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13661","last_updated":"2023-10-26T20:45:39Z","snapshot_observed_at":"2026-07-06T15:31:05.250637Z","submitted_at":"2023-05-23T04:10:26Z","title":"On the Risk of Misinformation Pollution with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13661","snapshot_observed_at":"2026-08-02T13:26:25.863764Z","title":"On the Risk of Misinformation Pollution with Large Language Models, October 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.863764Z"},"links":{"cited_paper":"/paper/2305.13661","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:9e6a2679ea5ca4dbc2efaecbeb7ea7a3692d63c7630f17d598be5db5ae10b865","observation_id":"cc6b1b18-4780-49c2-919b-bbe5ade5d68e","resolution":{"observed_at":"2026-08-02T13:26:25.863764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:25.968701Z","title":"Who‘s Who: Large Lan- guage Models Meet Knowledge Conflicts in Practice","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:25.968701Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:1f63b142729e16cb262b7d234752a7c2f1fe101892afd07b14d0900e5843b9ab","observation_id":"782890cf-73c9-4df6-80bf-d49a2673de6e","resolution":{"observed_at":"2026-08-02T13:26:25.968701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15896","last_updated":"2025-02-13T14:07:25Z","snapshot_observed_at":"2026-07-06T20:10:56.727212Z","submitted_at":"2024-12-20T13:50:18Z","title":"Evaluation of Reliability Criteria for News Publishers with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15896","snapshot_observed_at":"2026-08-02T13:26:26.125198Z","title":"Evaluation of Reliability Criteria for News Publishers with Large Language Models, February 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.125198Z"},"links":{"cited_paper":"/paper/2412.15896","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:cace015fd07f09ddde82e85b568c663146a2d6c127f6d30d2bcd0170b315d80b","observation_id":"e5805c07-6c15-42df-bb2d-f59734392cb2","resolution":{"observed_at":"2026-08-02T13:26:26.125198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18018","last_updated":"2023-10-27T09:48:29Z","snapshot_observed_at":"2026-08-07T21:43:48.165854Z","submitted_at":"2023-10-27T09:48:29Z","title":"NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18018","snapshot_observed_at":"2026-08-02T13:26:26.237664Z","title":"NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark, October 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.237664Z"},"links":{"cited_paper":"/paper/2310.18018","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:3e08ca9f04c987faea3bbf91b737d3373eea38966b42e276cad5b95462278eac","observation_id":"f07d090d-375a-4152-ad26-b306a029ab47","resolution":{"observed_at":"2026-08-02T13:26:26.237664Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:26.341360Z","title":"The spread of low-credibility content by social bots.Nature Communications, 9(1):4787, November 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.341360Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:1afdcc108481b458a0d8001cf2eae87a269f2ac508fcab97b434cd43f4be85d5","observation_id":"16f95c4d-27b8-4bfa-b30a-d6a57c14ecab","resolution":{"observed_at":"2026-08-02T13:26:26.341360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.13548","last_updated":"2025-05-10T07:10:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-20T14:46:48Z","title":"Towards Understanding Sycophancy in Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.13548","snapshot_observed_at":"2026-08-02T13:26:26.503530Z","title":"Bowman, Newton Cheng, Esin Durmus, Zac Hatfield-Dodds, Scott R","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.503530Z"},"links":{"cited_paper":"/paper/2310.13548","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:87b1894a6efa5394dcec81ab0128b135a67e136e9f446766fbd5e78fe16b95b0","observation_id":"3969ce7e-4009-45e7-a108-748d48b281aa","resolution":{"observed_at":"2026-08-02T13:26:26.503530Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:26.669266Z","title":"Mayer, and Padhraic Smyth","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.669266Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:ec0f6e995f369c74537738ac690cc7db88e7aa030d0925ef9c25fcd6858e22d7","observation_id":"9444d3fd-172a-403f-8c84-4bf3519b1833","resolution":{"observed_at":"2026-08-02T13:26:26.669266Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05355","last_updated":"2018-12-18T10:58:20Z","snapshot_observed_at":"2026-07-06T06:28:16.475418Z","submitted_at":"2018-03-14T15:30:37Z","title":"FEVER: a large-scale dataset for Fact Extraction and VERification","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.05355","snapshot_observed_at":"2026-08-02T13:26:26.833545Z","title":"FEVER: a large-scale dataset for Fact Extraction and VERification, December 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.833545Z"},"links":{"cited_paper":"/paper/1803.05355","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:4bb325450f9dd623022cedddc4be84bfffba3f33e189292a74f506a1fca7e52d","observation_id":"7175dfde-268d-4c45-b204-692b8bcaf3c6","resolution":{"observed_at":"2026-08-02T13:26:26.833545Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07176","last_updated":"2025-05-31T04:07:21Z","snapshot_observed_at":"2026-08-08T23:47:25.246943Z","submitted_at":"2024-10-09T17:59:58Z","title":"Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07176","snapshot_observed_at":"2026-08-02T13:26:26.999822Z","title":"Astute RAG: Overcom- ing Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models, May 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:26.999822Z"},"links":{"cited_paper":"/paper/2410.07176","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:21a10a5ea05c569bc88a575c0e9015694510e3747b9f9aa882b8114cf67b9bda","observation_id":"25715357-4196-495c-bdbb-ef85e0b16aa9","resolution":{"observed_at":"2026-08-02T13:26:26.999822Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10198","last_updated":"2025-02-07T05:11:18Z","snapshot_observed_at":"2026-08-08T08:08:45.905396Z","submitted_at":"2024-04-16T00:43:03Z","title":"ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10198","snapshot_observed_at":"2026-08-02T13:26:27.120009Z","title":"ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.120009Z"},"links":{"cited_paper":"/paper/2404.10198","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:17dba08710b76893fa103309701763338527021638457d34a3bac0e514c1baa1","observation_id":"0c3c4960-c756-4576-b6ec-4b9e55d6d82a","resolution":{"observed_at":"2026-08-02T13:26:27.120009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.09085","last_updated":"2024-05-31T15:13:33Z","snapshot_observed_at":"2026-07-06T17:01:49.058644Z","submitted_at":"2023-12-14T16:16:50Z","title":"The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09085","snapshot_observed_at":"2026-08-02T13:26:27.229026Z","title":"Lin, Shujian Yang, Tianqi Zhang, Weiyan Shi, Tianwei Zhang, Zhixuan Fang, Wei Xu, and Han Qiu","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.229026Z"},"links":{"cited_paper":"/paper/2312.09085","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:b76967b593090b68767d4de6f83e49b72870292e8caa8e2594c7a01a874741ab","observation_id":"1275e1b5-6242-4566-9eb9-0a14121ec2d3","resolution":{"observed_at":"2026-08-02T13:26:27.229026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:27.347237Z","title":"Knowledge Conflicts for LLMs: A Survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.347237Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:6b710d80fe65a27b193c5f2b9e8fa6be03785ce057ae7c0f2956067cc397c8bc","observation_id":"788711dd-310c-4a14-9c11-a920031406fd","resolution":{"observed_at":"2026-08-02T13:26:27.347237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:27.478427Z","title":"Accuracy and Political Bias of News Source Credibility Ratings by Large Language Models, February 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.478427Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:b62c2df27cc73812b746dee75ed489e33d1fcb995ce75878186df871fcc1c46f","observation_id":"7bab14bc-c582-44ac-821c-7e502f117296","resolution":{"observed_at":"2026-08-02T13:26:27.478427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14197","last_updated":"2025-01-27T08:51:16Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T01:08:39Z","title":"Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.14197","snapshot_observed_at":"2026-08-02T13:26:27.643188Z","title":"Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models, January 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.643188Z"},"links":{"cited_paper":"/paper/2312.14197","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:ce3b4ee2f7c928fb6739e4403e5e59cdd962c31ba6aa6d64bf5d5b1da2951227","observation_id":"322d5c44-c7ab-417d-9221-8c2d96b559fe","resolution":{"observed_at":"2026-08-02T13:26:27.643188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.11315","last_updated":"2023-10-23T03:25:13Z","snapshot_observed_at":"2026-08-02T03:24:19.101300Z","submitted_at":"2023-03-20T17:54:58Z","title":"Context-faithful Prompting for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.11315","snapshot_observed_at":"2026-08-02T13:26:27.749590Z","title":"twenty-two","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.749590Z"},"links":{"cited_paper":"/paper/2303.11315","citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:3277016abb9be1289f99a548949dc63028ed5f626ef2db9bac2691c43fd50616","observation_id":"b296fefb-1d1d-4cfe-aa4d-17364221ece0","resolution":{"observed_at":"2026-08-02T13:26:27.749590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:27.905294Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:27.905294Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:d847b3aeb095c828d22f6671cd6fe623f08a460b914477919b9588d347ee292e","observation_id":"fdeac60f-48e5-4e37-823c-2ed31d6e55d0","resolution":{"observed_at":"2026-08-02T13:26:27.905294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:28.015328Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:28.015328Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:6f322e43589ee8973c1872ca70056616e11e1eaf4fc4c70537787ba56953d4f2","observation_id":"d04cd2af-6c4a-483b-b1b5-301af319704b","resolution":{"observed_at":"2026-08-02T13:26:28.015328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:28.089527Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:28.089527Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:614ff62d6d71f6c86055a7476c196b44a6fcaa48306adabab2cc34135679c442","observation_id":"98584fe1-c468-43a9-8465-9525cc0e9583","resolution":{"observed_at":"2026-08-02T13:26:28.089527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:28.196531Z","title":"commitment check","venue":null,"work_id":null,"year":1948},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:28.196531Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:b747b75a21beb94501d35e8bdbf2a2a689a420f8369d521475a0d57dcbf3a12b","observation_id":"c3625542-033f-4ab2-9160-98a0b21736e2","resolution":{"observed_at":"2026-08-02T13:26:28.196531Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T13:26:28.271210Z","title":"We obtained informed consent before participants continued","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-02T13:26:28.271210Z"},"links":{"citing_paper":"/paper/2607.19355"},"observation_digest":"sha256:a35770f3c9f99532e462c0ebe4a94b8ca0ea7fdf5e281f4cc5be24b99183dde5","observation_id":"78082add-684c-4d57-897d-36488a303290","resolution":{"observed_at":"2026-08-02T13:26:28.271210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.19355","last_updated":"2026-05-22T12:13:16Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T21:44:05.596114Z","submitted_at":"2026-05-22T12:13:16Z","title":"Information Discernment in Large Language Models"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":37},"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 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2607.19355."}