{"as_of":"2026-08-18T23:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:21b2abe8557cdaa927fad5db3b893f54f6e0f0b92864c8c5b5b016dcfa4053bd","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":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":16,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:15:15.978088Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":2,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-12T18:15:15.978088Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11761","last_updated":"2025-02-20T16:22:19Z","snapshot_observed_at":"2026-08-15T08:34:22.985905Z","submitted_at":"2024-11-18T17:40:42Z","title":"Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework","version":2},"reference_index":171,"source":"pdf_text","source_observed_at":"2026-08-12T18:15:15.978088Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2411.11761"},"observation_digest":"sha256:e8ebaba316a98581572d35f2100835027cf808e0855a1d9ce6d6ce5ba6b8e093","observation_id":"1f529d69-7010-4884-8f41-2a12335c311a","resolution":{"observed_at":"2026-08-12T18:15:15.978088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-11T22:06:51.247150Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF, December 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03822","last_updated":"2024-12-05T02:35:46Z","snapshot_observed_at":"2026-08-18T04:19:06.016742Z","submitted_at":"2024-12-05T02:35:46Z","title":"Beyond the Binary: Capturing Diverse Preferences With Reward Regularization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T22:06:51.247150Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2412.03822"},"observation_digest":"sha256:b3475800a468ace93712af24d09445b416299acbcac05080987a3b1c3ecef881","observation_id":"23783648-074d-49db-887b-bd1fdb950640","resolution":{"observed_at":"2026-08-11T22:06:51.247150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2412.08812","last_updated":"2026-04-19T16:29:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-11T23:02:26Z","title":"Test-Time Alignment via Hypothesis Reweighting","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-05-23T06:55:54.051821Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2412.08812"},"observation_digest":"sha256:a9506ca0b46b800cd3ed6383a9a684a28a59b7ecc228865f777ce3054ed1842d","observation_id":"c0531dae-9d5b-44ea-8ec1-4e8c62143004","resolution":{"observed_at":"2026-05-23T06:57:40.535424Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-10T20:15:11.833637Z","title":"Siththaranjan, C","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.09254","last_updated":"2025-01-16T02:43:44Z","snapshot_observed_at":"2026-08-13T06:35:26.129901Z","submitted_at":"2025-01-16T02:43:44Z","title":"Clone-Robust AI Alignment","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T20:15:11.833637Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2501.09254"},"observation_digest":"sha256:38d6c9f8ef75064b4f1effa54c126ebade01601bf18eafa28f16b3cfc952adcf","observation_id":"60d3818d-8a1a-445f-bb9a-ecb28acf6327","resolution":{"observed_at":"2026-08-10T20:15:11.833637Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-10T15:18:19.167631Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.14294","last_updated":"2025-03-02T06:49:21Z","snapshot_observed_at":"2026-08-17T13:24:00.868239Z","submitted_at":"2025-01-24T07:24:23Z","title":"Examining Alignment of Large Language Models through Representative Heuristics: The Case of Political Stereotypes","version":3},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-10T15:18:19.167631Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2501.14294"},"observation_digest":"sha256:61ddcafe1c4a52cb8f6c5a1b2af1abc3ede2f41e4c856e239040625200c26d75","observation_id":"d07cd496-0aa3-4874-aa36-cd583d2aca4a","resolution":{"observed_at":"2026-08-10T15:18:19.167631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-09T20:51:59.197859Z","title":"Distributional preference learning: Understanding and accounting for hidden context in RLHF","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.19266","last_updated":"2025-01-31T16:26:28Z","snapshot_observed_at":"2026-08-17T21:57:35.682066Z","submitted_at":"2025-01-31T16:26:28Z","title":"Jackpot! Alignment as a Maximal Lottery","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-09T20:51:59.197859Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2501.19266"},"observation_digest":"sha256:85e7950d345d63589e04f3e239093d5dfbaa644bc26ef07e9cc20390813f2163","observation_id":"a4dada43-e749-4918-a3d3-c68069742f65","resolution":{"observed_at":"2026-08-09T20:51:59.197859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-09T10:21:04.459437Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.06823","last_updated":"2025-02-05T09:06:02Z","snapshot_observed_at":"2026-08-18T20:09:04.385616Z","submitted_at":"2025-02-05T09:06:02Z","title":"CTR-Driven Advertising Image Generation with Multimodal Large Language Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T10:21:04.459437Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2502.06823"},"observation_digest":"sha256:10d21c59820dfd8f0ae7f8101cf0649bc3d517f17de8a1755be051becdc329fe","observation_id":"809a079d-4dea-4418-bbbf-009af9095b07","resolution":{"observed_at":"2026-08-09T10:21:04.459437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-07T12:49:10.543390Z","title":"Distributional preference learning: Understanding and accounting for hidden context in RLHF","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23749","last_updated":"2025-05-29T17:59:20Z","snapshot_observed_at":"2026-08-18T00:12:08.333733Z","submitted_at":"2025-05-29T17:59:20Z","title":"Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T12:49:10.543390Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2505.23749"},"observation_digest":"sha256:647ae5612f20eab916c4e99ba949f2f41339b9178f2d006cb1f54e55f149e52b","observation_id":"5d19d2f2-1c7b-4921-a9fd-08f0ea002ba9","resolution":{"observed_at":"2026-08-07T12:49:10.543390Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-07T01:04:32.028901Z","title":"Distributional preference learn- ing: Understanding and accounting for hidden context in RLHF.arXiv preprint arXiv:2312.08358,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.12350","last_updated":"2025-06-14T05:14:49Z","snapshot_observed_at":"2026-08-17T21:58:26.493624Z","submitted_at":"2025-06-14T05:14:49Z","title":"Theoretical Tensions in RLHF: Reconciling Empirical Success with Inconsistencies in Social Choice Theory","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T01:04:32.028901Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2506.12350"},"observation_digest":"sha256:3135681df89c32542dfd637ecc2cc33722b8235331c74c773181c3300314e3dd","observation_id":"699e2fc7-0744-4fe0-9bf4-189127a6bc72","resolution":{"observed_at":"2026-08-07T01:04:32.028901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-06T16:34:25.197977Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf.arXiv preprint arXiv:2312.08358,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.13158","last_updated":"2025-07-17T14:22:24Z","snapshot_observed_at":"2026-08-15T15:23:09.345799Z","submitted_at":"2025-07-17T14:22:24Z","title":"Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T16:34:25.197977Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2507.13158"},"observation_digest":"sha256:d5be7295f1a2744e4ff94af36bece526ad814a13311b188c406a2e09e18fb8e2","observation_id":"129db947-a33a-4513-93e2-67f981934587","resolution":{"observed_at":"2026-08-06T16:34:25.197977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T16:02:26.007783Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.19132","last_updated":"2025-08-26T15:34:17Z","snapshot_observed_at":"2026-08-17T23:06:49.509124Z","submitted_at":"2025-08-26T15:34:17Z","title":"Active Query Selection for Crowd-Based Reinforcement Learning","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-05T16:02:26.007783Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2508.19132"},"observation_digest":"sha256:a76f869a17ee40653b21bed8bb5fcb8955e9f549e0cab636d4e36c7922190c92","observation_id":"e20a2f2a-12a6-4e2e-8637-5519f87425ea","resolution":{"observed_at":"2026-08-05T16:02:26.007783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2604.03238","last_updated":"2026-05-29T23:39:37Z","snapshot_observed_at":"2026-08-18T01:23:34.171780Z","submitted_at":"2026-01-31T21:51:17Z","title":"RLHF May Not Reflect Genuine Preferences","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T08:39:08.880486Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2604.03238"},"observation_digest":"sha256:0bdceb97fcc71b98d60a0d85f4e0c7ecdbb1b294d9d493beeec24f0a70223a31","observation_id":"1abf0f85-8f73-4ef6-801e-8190f4448a73","resolution":{"observed_at":"2026-05-16T08:40:46.322374Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2604.09876","last_updated":"2026-04-10T20:05:51Z","snapshot_observed_at":"2026-08-11T11:04:47.404089Z","submitted_at":"2026-04-10T20:05:51Z","title":"Efficient Personalization of Generative User Interfaces","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-10T16:52:34.799158Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2604.09876"},"observation_digest":"sha256:c3b15581297d7e7ea0b0b94a7ca531a4df6cba070eb77280d76a20f46d23f305","observation_id":"4fc5fe13-7443-4442-8716-83ee117809d9","resolution":{"observed_at":"2026-05-11T08:00:57.559506Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2604.20805","last_updated":"2026-04-22T17:36:52Z","snapshot_observed_at":"2026-08-18T04:21:36.110970Z","submitted_at":"2026-04-22T17:36:52Z","title":"Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problem","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-09T23:02:34.564375Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2604.20805"},"observation_digest":"sha256:37ce30b64a5e0178ca5f2de32e319e86736ec5a9bf85a63bf1f889bff1efc9ff","observation_id":"06cf540a-7373-4691-b261-15b869a81079","resolution":{"observed_at":"2026-05-09T23:04:17.696412Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2606.09038","last_updated":"2026-06-08T05:10:05Z","snapshot_observed_at":"2026-08-16T14:05:07.005152Z","submitted_at":"2026-06-08T05:10:05Z","title":"Personalization Meets Safety:Mechanisms,Risks,and Mitigations in Personalized LLMs","version":1},"reference_index":186,"source":"pdf_text","source_observed_at":"2026-06-27T16:49:14.243931Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2606.09038"},"observation_digest":"sha256:564dea00e01c80ad1959a463296a1d98dfe34db7e6ee65bd7f02c43197d047ea","observation_id":"a4e556fa-f511-4cbe-b4cd-41ca01a10e4c","resolution":{"observed_at":"2026-06-27T16:51:06.005505Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF","version":2},"cited_work":{"arxiv_id":"2312.08358","doi":"10.48550/arxiv.2312.08358","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08358","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distributional preference learning: Understanding and accounting for hidden context in rlhf","venue":"arXiv (Cornell University)","work_id":"16df5963-c59c-48f9-8ce8-8c5aa35771b9","year":2023},"citing_paper":{"arxiv_id":"2606.11470","last_updated":"2026-08-10T19:13:02Z","snapshot_observed_at":"2026-08-14T23:09:31.705348Z","submitted_at":"2026-06-09T21:59:37Z","title":"The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes","version":1},"reference_index":215,"source":"arxiv_source","source_observed_at":"2026-06-27T12:59:51.091008Z"},"links":{"cited_paper":"/paper/2312.08358","citing_paper":"/paper/2606.11470"},"observation_digest":"sha256:016cf8aaad68d23b1371e631ce783d63662cf6e45cb66759b8b62527e69c6904","observation_id":"7c1484f3-54f5-4e27-b71b-48038f27c286","resolution":{"observed_at":"2026-07-03T05:57:41.259581Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.08358/citation-record","integrity":"/paper/2312.08358/integrity","json":"/paper/2312.08358/citation-record.json","paper":"/paper/2312.08358"},"outbound":[],"paper":{"arxiv_id":"2312.08358","last_updated":"2024-04-17T01:58:09Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T14:35:01.177259Z","submitted_at":"2023-12-13T18:51:34Z","title":"Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2312.08358."}