{"as_of":"2026-08-18T22:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:02860e0be820e3c2c578d84dc63321ab9c207ddb75aa7f0ca9133e3c66232918","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T16:26:28.333393Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2509.05605/citation-record","integrity":"/paper/2509.05605/integrity","json":"/paper/2509.05605/citation-record.json","paper":"/paper/2509.05605"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-15T16:26:28.077854Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.077854Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:3fefa57e41658bf171053352ba0aa5588389891822e98b7fe9dc1c62a985723a","observation_id":"66cf6ac5-e364-4eaf-bedd-224fbf9a02b9","resolution":{"observed_at":"2026-08-15T16:26:28.077854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-15T16:26:28.082915Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.082915Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:eaf32b47173a7b811d029c21aa2982e22b06c25d0d08c8cf90e571549d33537f","observation_id":"cdf17676-2052-4615-a015-06fcc0696441","resolution":{"observed_at":"2026-08-15T16:26:28.082915Z","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":"2026-08-15T16:26:28.087997Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.087997Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:72d7edcead2dd5f6727308fffc61ee1a8c935929ac1c0c8c30fe94385cb1f8ca","observation_id":"2e670908-0928-4ef4-acfc-9d51d7257c25","resolution":{"observed_at":"2026-08-15T16:26:28.087997Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.138542Z","title":null,"venue":null,"work_id":"a3eb98ac-6f38-47ec-84bd-77538b0b7da9","year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.092293Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:83ba8482c1427b4419415ef3f841fe6fb5936cd9c813139f3f654c1769c1efe6","observation_id":"9184842c-6ea2-4e13-baf6-0a9d6477f4c8","resolution":{"observed_at":"2026-08-15T16:26:29.142674Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-15T16:26:28.096652Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.096652Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:196c654d1a3f11530e3d9b2046b70f8267e7bc6d1c5d8d14b7e216b8104f1f61","observation_id":"9330844c-8772-43f5-9c0c-a05bf4dabdbd","resolution":{"observed_at":"2026-08-15T16:26:28.096652Z","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":"2026-08-15T16:26:28.100887Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.100887Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:f5600cb81412eb30c980944e996a43137f4e0b4c4623d791f27f61f413d8ff20","observation_id":"e5850e99-6e4a-4aef-a3eb-123cdc7cbed8","resolution":{"observed_at":"2026-08-15T16:26:28.100887Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.01335","last_updated":"2024-06-14T21:17:17Z","snapshot_observed_at":"2026-08-15T08:59:30.302596Z","submitted_at":"2024-01-02T18:53:13Z","title":"Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.01335","snapshot_observed_at":"2026-08-15T16:26:28.105415Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.105415Z"},"links":{"cited_paper":"/paper/2401.01335","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:45116ccf5b09c37ac702be3e3edb74999a701aa588ceae4220fe1c19ab532812","observation_id":"1dcc3079-23e6-4eed-bbdc-6585e841c9cc","resolution":{"observed_at":"2026-08-15T16:26:28.105415Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11605","last_updated":"2025-03-16T09:43:15Z","snapshot_observed_at":"2026-08-16T16:55:47.412176Z","submitted_at":"2024-12-16T09:47:43Z","title":"SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.11605","snapshot_observed_at":"2026-08-15T16:26:28.109702Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.109702Z"},"links":{"cited_paper":"/paper/2412.11605","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:4cbe77f3380d3997bed544bff0b45b2a1319a87a791cb27780b9862df28ebb70","observation_id":"ad62c2ad-16cb-4875-87c4-a525c8d70a95","resolution":{"observed_at":"2026-08-15T16:26:28.109702Z","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":"2026-08-15T16:26:28.113882Z","title":"Glass, and Pengcheng He","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.113882Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:3c6f3713512af8b1800a6977187685118efd30201e8c67120209f805bbaf9a52","observation_id":"529fc7e9-1908-40e0-b5e4-88a4a1c9c449","resolution":{"observed_at":"2026-08-15T16:26:28.113882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01377","last_updated":"2024-07-16T03:24:39Z","snapshot_observed_at":"2026-08-14T00:28:11.851309Z","submitted_at":"2023-10-02T17:40:01Z","title":"UltraFeedback: Boosting Language Models with Scaled AI Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01377","snapshot_observed_at":"2026-08-15T16:26:28.117962Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.117962Z"},"links":{"cited_paper":"/paper/2310.01377","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:3347543b25fc6e44cac8a9ca942fc7075bab30a17772c6cafdd9e4424936e8d7","observation_id":"28129f54-96d9-464c-bd28-57364f2a0450","resolution":{"observed_at":"2026-08-15T16:26:28.117962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14233","last_updated":"2023-05-23T16:49:14Z","snapshot_observed_at":"2026-08-18T05:06:04.678949Z","submitted_at":"2023-05-23T16:49:14Z","title":"Enhancing Chat Language Models by Scaling High-quality Instructional Conversations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14233","snapshot_observed_at":"2026-08-15T16:26:28.122407Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.122407Z"},"links":{"cited_paper":"/paper/2305.14233","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:fd18ba8660c22fdaf2ff9f3973c7782990a05402ad785d34d56c9c7a72e10c4e","observation_id":"0dc989de-5001-4318-afe4-57189e6dcc74","resolution":{"observed_at":"2026-08-15T16:26:28.122407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18693","last_updated":"2025-05-27T11:56:56Z","snapshot_observed_at":"2026-08-18T11:14:44.856751Z","submitted_at":"2024-10-24T12:42:04Z","title":"Unleashing LLM Reasoning Capability via Scalable Question Synthesis from Scratch","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18693","snapshot_observed_at":"2026-08-15T16:26:28.126677Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.126677Z"},"links":{"cited_paper":"/paper/2410.18693","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:b7ed390b3969e224c434524f33d8cfa491b7d2b92286ac81228679ef30a16944","observation_id":"c0129569-0134-4805-94b0-874a94cc9bc1","resolution":{"observed_at":"2026-08-15T16:26:28.126677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06961","last_updated":"2024-10-09T14:57:31Z","snapshot_observed_at":"2026-08-16T13:11:04.470639Z","submitted_at":"2024-10-09T14:57:31Z","title":"Self-Boosting Large Language Models with Synthetic Preference Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06961","snapshot_observed_at":"2026-08-15T16:26:28.130817Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.130817Z"},"links":{"cited_paper":"/paper/2410.06961","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:64a25012dd6046999049c8579870a18043d94fc5073bd70c77751790b9c54853","observation_id":"827526c0-ccb4-4d65-8c1c-fd3bc4a72070","resolution":{"observed_at":"2026-08-15T16:26:28.130817Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08124","last_updated":"2024-12-18T03:22:31Z","snapshot_observed_at":"2026-08-16T13:43:47.653638Z","submitted_at":"2024-06-12T12:06:32Z","title":"Legend: Leveraging Representation Engineering to Annotate Safety Margin for Preference Datasets","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08124","snapshot_observed_at":"2026-08-15T16:26:28.135081Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.135081Z"},"links":{"cited_paper":"/paper/2406.08124","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:cd09cceccca7aa01b89c069f46c14dbed8e503881cf6c7c9932e49e1a1902931","observation_id":"b9e25239-6e6b-4202-b0ba-8344602acddb","resolution":{"observed_at":"2026-08-15T16:26:28.135081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11644","last_updated":"2023-10-02T06:12:30Z","snapshot_observed_at":"2026-08-13T11:19:55.436754Z","submitted_at":"2023-06-20T16:14:25Z","title":"Textbooks Are All You Need","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11644","snapshot_observed_at":"2026-08-15T16:26:28.139214Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.139214Z"},"links":{"cited_paper":"/paper/2306.11644","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:fde1593b8f7560b9121faca45e08a5bdb974a1d369137ed644bde2da3a13860c","observation_id":"05120fad-7583-4620-a656-2e67b7148c5a","resolution":{"observed_at":"2026-08-15T16:26:28.139214Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.108663Z","title":null,"venue":null,"work_id":"2520ff00-2abd-4944-b73b-2da5b0cd87e6","year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.143419Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:01622cd19dc71ed7353c87d753780c79c598091565c6370116c84013abc8d3ad","observation_id":"025ab5cd-d755-454f-9bdf-20fa5f48a748","resolution":{"observed_at":"2026-08-15T16:26:29.113051Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2403.01244","last_updated":"2024-05-25T12:17:29Z","snapshot_observed_at":"2026-08-16T14:13:28.768283Z","submitted_at":"2024-03-02T16:11:23Z","title":"Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.01244","snapshot_observed_at":"2026-08-15T16:26:28.147335Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.147335Z"},"links":{"cited_paper":"/paper/2403.01244","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:94169ef17f27992a443a263288ec7ef8c03d9405400257a13b0124972b3fe612","observation_id":"c5f22c5b-81ff-457a-b9e9-8f127504e2d2","resolution":{"observed_at":"2026-08-15T16:26:28.147335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.04089","last_updated":"2023-03-31T15:27:01Z","snapshot_observed_at":"2026-08-13T03:27:01.609831Z","submitted_at":"2022-12-08T05:50:53Z","title":"Editing Models with Task Arithmetic","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.04089","snapshot_observed_at":"2026-08-15T16:26:28.151613Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.151613Z"},"links":{"cited_paper":"/paper/2212.04089","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:617f5fc2d807116165f420378b663c271786475a9317c7a0d1f03234ed56b8c3","observation_id":"9c7c6a5c-d27d-4e3a-af12-1118a9374e9c","resolution":{"observed_at":"2026-08-15T16:26:28.151613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.10702","last_updated":"2023-11-20T02:01:33Z","snapshot_observed_at":"2026-08-18T15:11:49.913463Z","submitted_at":"2023-11-17T18:45:45Z","title":"Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.10702","snapshot_observed_at":"2026-08-15T16:26:28.155957Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.155957Z"},"links":{"cited_paper":"/paper/2311.10702","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:3f9402ff7a0c78bf2897c37e61bcac018331cdb28172a7c6a42d34baa859cd3b","observation_id":"b39543e8-506b-4790-9fcd-20abcb4732c3","resolution":{"observed_at":"2026-08-15T16:26:28.155957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02416","last_updated":"2024-11-02T10:01:38Z","snapshot_observed_at":"2026-08-16T14:21:44.715594Z","submitted_at":"2024-02-04T09:24:51Z","title":"Aligner: Efficient Alignment by Learning to Correct","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02416","snapshot_observed_at":"2026-08-15T16:26:28.160021Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.160021Z"},"links":{"cited_paper":"/paper/2402.02416","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:0d9e6d0ca2f7c7fbed8cfacdbcab489cb4ad109370563817d10a7217b2965ea5","observation_id":"ed2b16a6-e50d-4d97-8481-959b12427a30","resolution":{"observed_at":"2026-08-15T16:26:28.160021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04412","last_updated":"2025-03-04T00:04:24Z","snapshot_observed_at":"2026-08-16T13:45:23.876597Z","submitted_at":"2024-06-06T18:01:02Z","title":"Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04412","snapshot_observed_at":"2026-08-15T16:26:28.164132Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.164132Z"},"links":{"cited_paper":"/paper/2406.04412","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:5748265c45a3ebce00f63024e57bbd9d2e8a0b3aa5fe76cc5f23f8b5cae90cd0","observation_id":"1e2647a7-ae0f-4d91-ab5a-4fddeb433b5a","resolution":{"observed_at":"2026-08-15T16:26:28.164132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13064","last_updated":"2024-02-20T15:00:35Z","snapshot_observed_at":"2026-08-16T14:16:55.768718Z","submitted_at":"2024-02-20T15:00:35Z","title":"Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13064","snapshot_observed_at":"2026-08-15T16:26:28.168263Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.168263Z"},"links":{"cited_paper":"/paper/2402.13064","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:4fc4d0e90c0042e5055c13ca9851a61776e4509db2f9ca0bfcbcfb791f6370d0","observation_id":"38c95821-9801-48c7-af24-261acf5f0d59","resolution":{"observed_at":"2026-08-15T16:26:28.168263Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.095726Z","title":null,"venue":null,"work_id":"6831093a-9757-4dfd-94a7-2a2d3301572f","year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.172421Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:a0372548bfcb95d0a236073f2a9c41007fbe57b301057ca5a5ab6fadd88805db","observation_id":"01f9cf6c-beaf-49f1-893e-f12a54b3f944","resolution":{"observed_at":"2026-08-15T16:26:29.099814Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:28.176615Z","title":"Hashimoto","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.176615Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:ca78f8bfaab276f52fa56681cc636dea112329fe49948ed7658feab5b67a9bf2","observation_id":"1a10f64c-d628-43d3-87a3-ac3292aef1bc","resolution":{"observed_at":"2026-08-15T16:26:28.176615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09110","last_updated":"2023-10-01T21:44:23Z","snapshot_observed_at":"2026-08-10T23:10:13.900680Z","submitted_at":"2022-11-16T18:51:34Z","title":"Holistic Evaluation of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09110","snapshot_observed_at":"2026-08-15T16:26:28.180554Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.180554Z"},"links":{"cited_paper":"/paper/2211.09110","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:95c7d698780e5e57d925b07f207b589fdcde3afa28293c4f03fbae6054e03b9e","observation_id":"27ea4841-40c7-48ee-9621-fced0599f39e","resolution":{"observed_at":"2026-08-15T16:26:28.180554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18727","last_updated":"2024-10-03T20:09:31Z","snapshot_observed_at":"2026-08-18T18:11:00.612051Z","submitted_at":"2024-05-29T03:17:16Z","title":"CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18727","snapshot_observed_at":"2026-08-15T16:26:28.184749Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.184749Z"},"links":{"cited_paper":"/paper/2405.18727","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:a699e525d1bf6d409b7c1a2b32fc90bb146e05054fbde1b7f683d776abc8798c","observation_id":"f92d8037-876b-4bcd-8982-03d9791a4c34","resolution":{"observed_at":"2026-08-15T16:26:28.184749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15997","last_updated":"2024-07-03T05:21:02Z","snapshot_observed_at":"2026-08-16T14:31:36.997821Z","submitted_at":"2023-12-26T11:01:36Z","title":"Aligning Large Language Models with Human Preferences through Representation Engineering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15997","snapshot_observed_at":"2026-08-15T16:26:28.189157Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.189157Z"},"links":{"cited_paper":"/paper/2312.15997","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:b42cb87131b0010c53cbc25b747e4e1a0151e5dd355df22c04189576d6072b08","observation_id":"f4b40501-cf7f-4db8-979f-6c6a494664bc","resolution":{"observed_at":"2026-08-15T16:26:28.189157Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.074037Z","title":null,"venue":null,"work_id":"bf755113-7c6e-4013-8afc-d41a33081fcb","year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.193270Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:168e596fbaf0df0ad7a8102410a74183c78a14904ec7a3c113d920245ca1a699","observation_id":"5a2be0e1-423f-48a9-8a67-8811483321bd","resolution":{"observed_at":"2026-08-15T16:26:29.078397Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2405.14734","last_updated":"2024-11-01T20:05:19Z","snapshot_observed_at":"2026-08-16T13:50:07.192537Z","submitted_at":"2024-05-23T16:01:46Z","title":"SimPO: Simple Preference Optimization with a Reference-Free Reward","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14734","snapshot_observed_at":"2026-08-15T16:26:28.197031Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.197031Z"},"links":{"cited_paper":"/paper/2405.14734","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:0feae2a3e7ae261d5dca98bc129ca0124f6decb62714f2260cde03bcb2bc20e6","observation_id":"844276d1-41a8-416a-9280-a9e2de82f034","resolution":{"observed_at":"2026-08-15T16:26:28.197031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09332","last_updated":"2022-06-01T19:08:11Z","snapshot_observed_at":"2026-08-07T17:14:39.278754Z","submitted_at":"2021-12-17T05:43:43Z","title":"WebGPT: Browser-assisted question-answering with human feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.09332","snapshot_observed_at":"2026-08-15T16:26:28.201235Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.201235Z"},"links":{"cited_paper":"/paper/2112.09332","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:a0ff5150715e05566a7895d79a3d784b57694a0ab2cdadc795ff1d89dd099a5b","observation_id":"9e386091-3e8b-4de5-b2e5-dfc5a0ea95d6","resolution":{"observed_at":"2026-08-15T16:26:28.201235Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.060152Z","title":null,"venue":null,"work_id":"b469be88-43d3-4903-bdd1-f7b1feb40f9d","year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.205256Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:adef9a66bb5256584d2b06b1c71a6d34becf355774d1555871e4b60479430e80","observation_id":"53f79934-eba7-4cef-abcb-20f16e597f32","resolution":{"observed_at":"2026-08-15T16:26:29.064281Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:28.209141Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.209141Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:e9ce6b194a264c3f72582e88e0d105a666377cfe404572da3a3dabd5cb6a4051","observation_id":"0acd3a7c-3d69-4ce9-97af-0d078c6a4ce0","resolution":{"observed_at":"2026-08-15T16:26:28.209141Z","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":"2026-08-15T16:26:28.213160Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.213160Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:ff4d18b31558c612fbb8328a9eaef546d62e011389c1e129034d844271d2cadf","observation_id":"dbbe9980-6246-467f-a867-cbbd0eec6d06","resolution":{"observed_at":"2026-08-15T16:26:28.213160Z","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":"2026-08-15T16:26:28.217067Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.217067Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:0445cbfcc1c8784a5537b4bf45a520c7d8a0208ddb481cbc6ff27b5b4615e3de","observation_id":"91ff14f0-7105-44d0-8e0e-58382c039e89","resolution":{"observed_at":"2026-08-15T16:26:28.217067Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:29.021766Z","title":null,"venue":null,"work_id":"ef14a0db-b516-4f3f-b7e1-c00db161e5e8","year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.222201Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:cfc8554b63a3adaf646e612c6ee7a1f506dd0f1350eed7d4755638e0adb0fbcc","observation_id":"c26ac2cc-cf58-4694-ad3b-9b683f6bac3b","resolution":{"observed_at":"2026-08-15T16:26:29.026271Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:28.226231Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.226231Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:e60c692322b0df9d17ffeabebd4081e61cb0571b1ddd032b35020e7d7e807574","observation_id":"1c2c299d-2685-4036-902d-be10934c3d51","resolution":{"observed_at":"2026-08-15T16:26:28.226231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.09298","last_updated":"2025-02-12T21:57:06Z","snapshot_observed_at":"2026-08-16T13:34:44.187629Z","submitted_at":"2024-07-12T14:31:05Z","title":"Transformer Layers as Painters","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.09298","snapshot_observed_at":"2026-08-15T16:26:28.230057Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.230057Z"},"links":{"cited_paper":"/paper/2407.09298","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:c8e63d1e1043c0f522371f97366b8b89771ba481282c2b0574770718432ff298","observation_id":"f29b6e90-467a-4a53-94cd-d3e8faa8a9f9","resolution":{"observed_at":"2026-08-15T16:26:28.230057Z","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":"2026-08-15T16:26:28.234349Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.234349Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:61013721557c3968ccc7b80a41eebe2098416f6425647274448e2ebce5c8dd8d","observation_id":"f94abd80-195a-4736-9a48-d3e717cd2a93","resolution":{"observed_at":"2026-08-15T16:26:28.234349Z","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":"2026-08-15T16:26:28.238364Z","title":"Hashimoto","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.238364Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:2b5916a59ffba8103eeb4c79e5af150a154eb9b6717933ad2d1ea7ec2ba160f0","observation_id":"cc5a5e99-64cb-419f-8ae3-1f2d316e3d4d","resolution":{"observed_at":"2026-08-15T16:26:28.238364Z","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":"2026-08-15T16:26:28.242221Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.242221Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:118abdeca1024480653ab636bf5892cbee403000f15844bbd749419a48feb4c9","observation_id":"f699c2c4-ce71-466b-bd0f-67b962e34a02","resolution":{"observed_at":"2026-08-15T16:26:28.242221Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T16:26:28.981455Z","title":"Daniel Freeman, Theodore R","venue":null,"work_id":"c531e946-c2fa-4ebe-9067-a54f008120aa","year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.246014Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:0454fc73e702e7595e05f7e73b795cdeebf19614da731d4661af1f8d6bc9d9a7","observation_id":"52d026ba-6fd6-4e0e-85b7-70e56c2621a5","resolution":{"observed_at":"2026-08-15T16:26:28.986769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2404.12253","last_updated":"2024-12-10T18:19:29Z","snapshot_observed_at":"2026-08-17T03:24:15.091127Z","submitted_at":"2024-04-18T15:21:34Z","title":"Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12253","snapshot_observed_at":"2026-08-15T16:26:28.250013Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.250013Z"},"links":{"cited_paper":"/paper/2404.12253","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:d6ee68aea1b081879cca90ee99ba585d11d6ab621cface8eab17778e0f028dba","observation_id":"31044c9b-c5f4-4420-a51a-5e7b59f8bb1e","resolution":{"observed_at":"2026-08-15T16:26:28.250013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-15T16:26:28.254256Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.254256Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:7bade2e7b607bce1deb5e811efcb5621daa254952b1892faa8916e9e39825c5e","observation_id":"71a8e492-c989-48f9-bf03-c6ee3ae064ab","resolution":{"observed_at":"2026-08-15T16:26:28.254256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12845","last_updated":"2024-06-18T17:58:28Z","snapshot_observed_at":"2026-08-18T10:59:53.620358Z","submitted_at":"2024-06-18T17:58:28Z","title":"Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12845","snapshot_observed_at":"2026-08-15T16:26:28.258543Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.258543Z"},"links":{"cited_paper":"/paper/2406.12845","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:f1d805cea7ab2618e451f2ea7bb5c0143277386e2038d8ee8e6f42f9fc7671a4","observation_id":"3abe4705-e3ba-4589-bf49-2191e774d1ae","resolution":{"observed_at":"2026-08-15T16:26:28.258543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00368","last_updated":"2024-05-31T07:22:01Z","snapshot_observed_at":"2026-08-16T14:30:41.754354Z","submitted_at":"2023-12-31T02:13:18Z","title":"Improving Text Embeddings with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.00368","snapshot_observed_at":"2026-08-15T16:26:28.262513Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.262513Z"},"links":{"cited_paper":"/paper/2401.00368","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:a13f0baa111b18e999494e6c136cf9c93a5f4d2056f5ca582736f7854ae3fe2f","observation_id":"f29bbc14-9b95-48e3-94d1-d20bc83f40fe","resolution":{"observed_at":"2026-08-15T16:26:28.262513Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.02666","last_updated":"2024-08-08T17:09:58Z","snapshot_observed_at":"2026-08-18T20:05:45.096677Z","submitted_at":"2024-08-05T17:57:02Z","title":"Self-Taught Evaluators","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.02666","snapshot_observed_at":"2026-08-15T16:26:28.266680Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.266680Z"},"links":{"cited_paper":"/paper/2408.02666","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:f0a5b9ce7553fa8cd102f69c0d93cde2a8f3011ab0421223492031c3dbe6bc25","observation_id":"86556b56-1481-4737-939c-a1ab376e9b8a","resolution":{"observed_at":"2026-08-15T16:26:28.266680Z","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":"2026-08-15T16:26:28.270685Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.270685Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:f03c3d1476cccc7c4754a6d6b7edffbf3e839a529c8bf2ab23e0837c14614da3","observation_id":"5ac8f2ec-9ef7-4302-8c30-8edbec086fba","resolution":{"observed_at":"2026-08-15T16:26:28.270685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.04359","last_updated":"2021-12-08T16:09:48Z","snapshot_observed_at":"2026-08-09T15:17:43.394064Z","submitted_at":"2021-12-08T16:09:48Z","title":"Ethical and social risks of harm from Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.04359","snapshot_observed_at":"2026-08-15T16:26:28.274599Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.274599Z"},"links":{"cited_paper":"/paper/2112.04359","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:784578e014657735438902d107baf858b9674afc41203ae9d87b118f32504c46","observation_id":"2a9ad9c1-9123-4fe3-a4c9-e469c242c1f5","resolution":{"observed_at":"2026-08-15T16:26:28.274599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12822","last_updated":"2024-12-08T04:06:53Z","snapshot_observed_at":"2026-08-17T15:42:49.103733Z","submitted_at":"2024-09-19T14:50:34Z","title":"Language Models Learn to Mislead Humans via RLHF","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12822","snapshot_observed_at":"2026-08-15T16:26:28.278753Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.278753Z"},"links":{"cited_paper":"/paper/2409.12822","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:64afd0b1ef0a506cf42d064f5e5364820eb7287785741b05a70d03116ba102d6","observation_id":"f4b0f4fa-b604-42a8-98eb-15ad11b18e6b","resolution":{"observed_at":"2026-08-15T16:26:28.278753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.19594","last_updated":"2024-07-30T01:38:06Z","snapshot_observed_at":"2026-08-16T13:30:25.003501Z","submitted_at":"2024-07-28T21:58:28Z","title":"Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.19594","snapshot_observed_at":"2026-08-15T16:26:28.282926Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.282926Z"},"links":{"cited_paper":"/paper/2407.19594","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:b0112f39c491690ede9f562c6190a8b09ccac4f1a33ff36e715c262750e3d10b","observation_id":"0a9c9413-3d3a-4448-958a-096170e80aeb","resolution":{"observed_at":"2026-08-15T16:26:28.282926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12244","last_updated":"2025-05-27T06:49:09Z","snapshot_observed_at":"2026-08-13T02:06:18.586697Z","submitted_at":"2023-04-24T16:31:06Z","title":"WizardLM: Empowering large pre-trained language models to follow complex instructions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12244","snapshot_observed_at":"2026-08-15T16:26:28.287446Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.287446Z"},"links":{"cited_paper":"/paper/2304.12244","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:5e4dd99f0ee9c2a65d2d4b856b2515485e08c8d2cafb0cfde461e5531326070a","observation_id":"72ade002-bab1-40f0-92c5-d8d95c574586","resolution":{"observed_at":"2026-08-15T16:26:28.287446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08464","last_updated":"2024-10-07T01:45:38Z","snapshot_observed_at":"2026-08-12T12:16:58.791696Z","submitted_at":"2024-06-12T17:52:30Z","title":"Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08464","snapshot_observed_at":"2026-08-15T16:26:28.291535Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.291535Z"},"links":{"cited_paper":"/paper/2406.08464","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:41bca13c3dacdeeca5a5fb38f3a6a7fb5a22bb9ea3ec1e99dcfbf2f43a6d94fe","observation_id":"b8efebee-8cf5-444f-82b4-ec0e0de00563","resolution":{"observed_at":"2026-08-15T16:26:28.291535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.04850","last_updated":"2023-11-11T05:11:18Z","snapshot_observed_at":"2026-08-16T14:44:53.286559Z","submitted_at":"2023-11-08T17:35:20Z","title":"Rethinking Benchmark and Contamination for Language Models with Rephrased Samples","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.04850","snapshot_observed_at":"2026-08-15T16:26:28.295748Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.295748Z"},"links":{"cited_paper":"/paper/2311.04850","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:7acbccc16fa97fd031133d38f5c9ed488c7256d88190a1e3a48cd0cf76ee995c","observation_id":"081e16bc-34c9-4643-bd6c-44f61643b2e9","resolution":{"observed_at":"2026-08-15T16:26:28.295748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13669","last_updated":"2024-05-28T06:39:17Z","snapshot_observed_at":"2026-08-16T14:16:40.183073Z","submitted_at":"2024-02-21T10:06:08Z","title":"Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13669","snapshot_observed_at":"2026-08-15T16:26:28.299762Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.299762Z"},"links":{"cited_paper":"/paper/2402.13669","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:41cb6d1ce61d6310bbde518059089ed37224db3aa8219bad237f477bc8c7e583","observation_id":"cff26305-7447-474e-91a4-c5fda0a5799b","resolution":{"observed_at":"2026-08-15T16:26:28.299762Z","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":"2026-08-15T16:26:28.304020Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.304020Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:ff5c197839c194b4731af6239a8d9261dcf5809c23e7a1786420e9120999d4be","observation_id":"9e05a5bf-779d-4ae6-b276-58af7a81de00","resolution":{"observed_at":"2026-08-15T16:26:28.304020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03816","last_updated":"2024-11-18T05:36:16Z","snapshot_observed_at":"2026-08-16T18:17:36.314960Z","submitted_at":"2024-06-06T07:40:00Z","title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03816","snapshot_observed_at":"2026-08-15T16:26:28.307933Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.307933Z"},"links":{"cited_paper":"/paper/2406.03816","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:26f3452f8d495844556bdcbfcc83eea50c19cdf17abedecf0705ac5f647079bb","observation_id":"d7bd3656-d3c4-4d7e-bdca-adc3cee26df6","resolution":{"observed_at":"2026-08-15T16:26:28.307933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17811","last_updated":"2024-06-05T11:15:04Z","snapshot_observed_at":"2026-08-16T14:14:53.732860Z","submitted_at":"2024-02-27T14:45:04Z","title":"TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17811","snapshot_observed_at":"2026-08-15T16:26:28.312016Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.312016Z"},"links":{"cited_paper":"/paper/2402.17811","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:9996ffd4481c2ccc37799cfb0f5fbab5f80ccd67caeb027aa3f876508e0e6a9c","observation_id":"84b31d12-c8d8-4a3f-807a-4bff65f89a7a","resolution":{"observed_at":"2026-08-15T16:26:28.312016Z","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":"2026-08-15T16:26:28.316269Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.316269Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:9acc7ae437d74e589eaa10cf5bc1aac8c7522418aff73807279aa86e1f3dc16a","observation_id":"3f29823c-e246-4938-abf1-fe746c40fe39","resolution":{"observed_at":"2026-08-15T16:26:28.316269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.13372","last_updated":"2024-06-27T22:44:48Z","snapshot_observed_at":"2026-08-17T02:51:06.474773Z","submitted_at":"2024-03-20T08:08:54Z","title":"LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.13372","snapshot_observed_at":"2026-08-15T16:26:28.320793Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.320793Z"},"links":{"cited_paper":"/paper/2403.13372","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:ff54a8cab9c8930312e5d1415d256af46590b641a4ba7d473af6d650cd5065d8","observation_id":"7045ec7b-c87c-4e50-972b-5c28e6e7fa43","resolution":{"observed_at":"2026-08-15T16:26:28.320793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01405","last_updated":"2025-03-03T06:14:14Z","snapshot_observed_at":"2026-07-06T16:26:38.284922Z","submitted_at":"2023-10-02T17:59:07Z","title":"Representation Engineering: A Top-Down Approach to AI Transparency","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01405","snapshot_observed_at":"2026-08-15T16:26:28.324931Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.324931Z"},"links":{"cited_paper":"/paper/2310.01405","citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:045dc174719aa239251e2117cea98e5936f1e2f471487b57863087970628b24d","observation_id":"9c183357-56c7-4558-9331-d03f8f8dd81f","resolution":{"observed_at":"2026-08-15T16:26:28.324931Z","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":"2026-08-15T16:26:28.328967Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.328967Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:07f1501c17d0ee98590bcaf58fa9707e3fce2e2e72191383fe0250788c0e6557","observation_id":"47874377-6f59-4226-82bb-ed1cf87b9a1c","resolution":{"observed_at":"2026-08-15T16:26:28.328967Z","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":"2026-08-15T16:26:28.333393Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-15T16:26:28.333393Z"},"links":{"citing_paper":"/paper/2509.05605"},"observation_digest":"sha256:ff42a96cf03b802413974ed39d83439058f07030b63c19f7f55ef57755f84f04","observation_id":"b724e026-3dfe-4368-9071-c7d4dabe1eab","resolution":{"observed_at":"2026-08-15T16:26:28.333393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.05605","last_updated":"2025-09-06T05:38:47Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-18T01:09:45.893295Z","submitted_at":"2025-09-06T05:38:47Z","title":"Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":61,"verified_exact":0,"verified_fuzzy":1},"total_outbound_references":62},"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 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2509.05605."}