{"as_of":"2026-08-09T23:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:07200e0da214140003db3472aec1cd09b54a00e67de99188bf389421cc9190d2","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":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":31,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T16:20:57.809166Z","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":4,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"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":63,"source":"arxiv_source","source_observed_at":"2026-05-23T06:55:54.051821Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2412.08812"},"observation_digest":"sha256:7bcfba7d1c30cf640ae1fe12b22a85c9fa2fe943908c7132d45e3877ca71f104","observation_id":"598f01aa-8703-463d-8bbb-a76cc672583a","resolution":{"observed_at":"2026-05-23T06:57:40.429509Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-09T16:20:57.809166Z","title":"D., and Potts, C","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.01179","last_updated":"2025-05-29T14:57:31Z","snapshot_observed_at":"2026-08-09T16:14:55.797133Z","submitted_at":"2025-02-03T09:13:09Z","title":"Joint Localization and Activation Editing for Low-Resource Fine-Tuning","version":4},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-09T16:20:57.809166Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2502.01179"},"observation_digest":"sha256:8714969f3008a585d6efa33f0ebf71f5dcc638e48f1ff09a67d66c2dd0858915","observation_id":"1fd65537-ce4e-46e7-a1a5-dbe453f87bf5","resolution":{"observed_at":"2026-08-09T16:20:57.809166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-08T21:06:56.089277Z","title":"Reft: Representation finetuning for language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05242","last_updated":"2026-05-27T09:11:42Z","snapshot_observed_at":"2026-08-08T20:58:31.381100Z","submitted_at":"2025-02-07T13:25:33Z","title":"Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-08T21:06:56.089277Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2502.05242"},"observation_digest":"sha256:fbd6c678106e4be14e3dfa46a2679ae4cd06145aef2ba21e90570e36eeaaf8c3","observation_id":"98241810-e6fc-4da6-b8c2-fdd71696400b","resolution":{"observed_at":"2026-08-08T21:06:56.089277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-08T17:03:50.273157Z","title":"Man- ning, and Christopher Potts","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06029","last_updated":"2025-06-01T13:34:36Z","snapshot_observed_at":"2026-08-09T04:47:46.789215Z","submitted_at":"2025-02-09T21:05:11Z","title":"DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-08T17:03:50.273157Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2502.06029"},"observation_digest":"sha256:3cff4b3a20106bf60339799a47f0442369bca0ea40fbf6a88ac71028742fd224","observation_id":"55a09c00-fef4-4e4e-9f8a-8f0d3a06d894","resolution":{"observed_at":"2026-08-08T17:03:50.273157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-08T14:13:38.389705Z","title":"D., and Potts, C","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06975","last_updated":"2025-02-10T19:14:51Z","snapshot_observed_at":"2026-08-08T23:51:33.892065Z","submitted_at":"2025-02-10T19:14:51Z","title":"Position: Episodic Memory is the Missing Piece for Long-Term LLM Agents","version":1},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-08T14:13:38.389705Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2502.06975"},"observation_digest":"sha256:c6c05174484129dcbf81a35097aeb1d0da473437f9d32ae34c8ed7a5dde067e3","observation_id":"9da03f27-8ed8-4025-aa89-493f05aa0b36","resolution":{"observed_at":"2026-08-08T14:13:38.389705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2504.01990","last_updated":"2025-08-02T12:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-31T18:00:29Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-22T21:39:49.832151Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2504.01990"},"observation_digest":"sha256:2916eefee1116e4db96387d296ecd1ce1c49bb33686e0523e3fdcf2dad931896","observation_id":"f3eb90b6-7c7d-4dbc-99ea-16ae47033623","resolution":{"observed_at":"2026-05-22T21:42:10.520758Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-07T15:05:18.938632Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.17153","last_updated":"2025-05-22T11:27:01Z","snapshot_observed_at":"2026-08-08T08:42:49.400073Z","submitted_at":"2025-05-22T11:27:01Z","title":"Amplify Adjacent Token Differences: Enhancing Long Chain-of-Thought Reasoning with Shift-FFN","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T15:05:18.938632Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2505.17153"},"observation_digest":"sha256:2176e9bb89e8e16c34b01571c62cbd3ab284da1f7df480ff9c432f7ce386b797","observation_id":"50c6d867-dd34-4e29-b1ff-b321fb8aa9d0","resolution":{"observed_at":"2026-08-07T15:05:18.938632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-07T13:51:33.386643Z","title":"Manning, and Christopher Potts","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20809","last_updated":"2025-05-27T07:16:40Z","snapshot_observed_at":"2026-08-07T21:54:12.571328Z","submitted_at":"2025-05-27T07:16:40Z","title":"Improved Representation Steering for Language Models","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T13:51:33.386643Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2505.20809"},"observation_digest":"sha256:cbb4d3323d70af86f982509c7216dec0f0e55fd7bfb166096f317c8192d5793f","observation_id":"b6492f5f-0acb-4fb3-8926-87e8a136e00f","resolution":{"observed_at":"2026-08-07T13:51:33.386643Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-07T12:18:55.792408Z","title":"A Motivating the Studying of Dropout Through Knowledge Storage The central claim of Hinton et al","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.24788","last_updated":"2025-05-30T16:48:38Z","snapshot_observed_at":"2026-08-07T12:11:15.878396Z","submitted_at":"2025-05-30T16:48:38Z","title":"Drop Dropout on Single-Epoch Language Model Pretraining","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T12:18:55.792408Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2505.24788"},"observation_digest":"sha256:15fd7098f1fd4dc757ec74264d2e92fa359c5afc8ebca26fb00c92460c13bff1","observation_id":"3f795873-d19c-46f8-9103-0ee8f35cf793","resolution":{"observed_at":"2026-08-07T12:18:55.792408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-06T19:57:44.494978Z","title":"D., and Potts, C","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04250","last_updated":"2025-07-06T05:47:04Z","snapshot_observed_at":"2026-08-09T00:28:34.913528Z","submitted_at":"2025-07-06T05:47:04Z","title":"Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T19:57:44.494978Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2507.04250"},"observation_digest":"sha256:e5685134b0fd680d2ced56275b63fb0c4d0ba52771bf3cea6088e78e802f1897","observation_id":"a418dee3-7334-447b-b896-45a9f0069e5e","resolution":{"observed_at":"2026-08-06T19:57:44.494978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-06T17:52:37.821689Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.10085","last_updated":"2025-07-14T09:11:33Z","snapshot_observed_at":"2026-08-08T11:30:55.213065Z","submitted_at":"2025-07-14T09:11:33Z","title":"Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T17:52:37.821689Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2507.10085"},"observation_digest":"sha256:8ccf510ebcfa25d5cc06a62bcc8da432ab618dda2f7d81bf089303c90f7c2a3e","observation_id":"82e2e057-d0e1-417f-8d07-f07a05d2bf59","resolution":{"observed_at":"2026-08-06T17:52:37.821689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-06T13:56:31.443834Z","title":"Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atti- cus Geiger, Dan Jurafsky, Christopher D Manning, and Christopher Potts","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20046","last_updated":"2025-07-26T19:38:46Z","snapshot_observed_at":"2026-08-08T20:59:21.131516Z","submitted_at":"2025-07-26T19:38:46Z","title":"Infogen: Generating Complex Statistical Infographics from Documents","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T13:56:31.443834Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2507.20046"},"observation_digest":"sha256:b1604db505539c1a7912f1236d07b041cd9cba3486440b97631aedea6adec1b0","observation_id":"493d3f4d-1267-41c4-b8a4-1543c6c5be7b","resolution":{"observed_at":"2026-08-06T13:56:31.443834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-04T21:01:50.159542Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08255","last_updated":"2025-09-10T03:20:56Z","snapshot_observed_at":"2026-08-07T23:55:40.448001Z","submitted_at":"2025-09-10T03:20:56Z","title":"Mitigating Catastrophic Forgetting in Large Language Models with Forgetting-aware Pruning","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-04T21:01:50.159542Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2509.08255"},"observation_digest":"sha256:b393d8d0223462ca773f8a7ce07465ae052b032d649616d15ce4bc3f157659ff","observation_id":"572e3f72-34eb-4b4e-bb4e-08b41562ffdd","resolution":{"observed_at":"2026-08-04T21:01:50.159542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2511.06516","last_updated":"2026-06-28T18:20:13Z","snapshot_observed_at":"2026-08-03T23:21:36.698338Z","submitted_at":"2025-11-09T19:58:24Z","title":"You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-21T18:46:04.926179Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2511.06516"},"observation_digest":"sha256:80cb00e2a279b206acbabb604dcb746d562b6c3b493581cf8ce403fb698574b9","observation_id":"4c019d95-7711-4638-9904-659a3c51afc6","resolution":{"observed_at":"2026-05-21T18:50:30.147028Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-03T23:21:37.760607Z","title":"Selective task arithmetic: Per-vector selection for robust model editing and merging","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.06516","last_updated":"2026-06-28T18:20:13Z","snapshot_observed_at":"2026-08-03T23:21:36.698338Z","submitted_at":"2025-11-09T19:58:24Z","title":"You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations","version":4},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-03T23:21:37.760607Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2511.06516"},"observation_digest":"sha256:9002974c33f6b20fa18b6cd7eb1d71b2f5823538c7984a9019d7acd06fb525d9","observation_id":"ec84154c-0c77-46fc-9396-3082fb9b47e0","resolution":{"observed_at":"2026-08-03T23:21:37.760607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-03T18:48:26.562615Z","title":"Wikimedia downloads.https://dumps.wikimedia.org","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.03661","last_updated":"2026-07-30T09:26:10Z","snapshot_observed_at":"2026-08-09T19:25:44.463940Z","submitted_at":"2025-12-03T10:50:15Z","title":"Dynamically Scaled Activation Steering","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T18:48:26.562615Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2512.03661"},"observation_digest":"sha256:0d1cb3049a90fb580539478c7d4cf9e005524038cf26346a0c1f209bbd7180db","observation_id":"c873a3cd-e5c0-4803-895f-b9c572445dbb","resolution":{"observed_at":"2026-08-03T18:48:26.562615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2604.17663","last_updated":"2026-04-19T23:26:02Z","snapshot_observed_at":"2026-07-06T23:04:41.564912Z","submitted_at":"2026-04-19T23:26:02Z","title":"ATLAS: Constitution-Conditioned Latent Geometry and Redistribution Across Language Models and Neural Perturbation Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T05:55:41.400468Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2604.17663"},"observation_digest":"sha256:6cff1a1371344678990819ba46700039ef787ec0119f293a1b57545427df9aee","observation_id":"7749e587-eb8f-49ae-b131-3b82309eb5ff","resolution":{"observed_at":"2026-05-10T05:56:10.964883Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.04980","last_updated":"2026-05-06T14:32:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-06T14:32:29Z","title":"Conceptors for Semantic Steering","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-05-08T17:16:25.761795Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.04980"},"observation_digest":"sha256:57cbd02d7895531ba3967ce36c4e0f22bd8b29d15611cdeeb99345c568f94456","observation_id":"e666dbb3-0936-47fd-8c8b-a1e1b8ad201c","resolution":{"observed_at":"2026-05-11T17:46:06.817414Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.05715","last_updated":"2026-05-07T05:58:38Z","snapshot_observed_at":"2026-07-06T23:18:17.333660Z","submitted_at":"2026-05-07T05:58:38Z","title":"Decodable but Not Corrected by Fixed Residual-Stream Linear Steering: Evidence from Medical LLM Failure Regimes","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-05-08T11:42:16.090162Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.05715"},"observation_digest":"sha256:4c2f1772d7ad4f64f63827aa264332870fa6ec951f14a535c11d3eb48d1af1dc","observation_id":"7c397001-3f97-4579-93ea-687ad3cd1b8a","resolution":{"observed_at":"2026-05-11T19:31:10.562160Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.07631","last_updated":"2026-05-08T11:59:13Z","snapshot_observed_at":"2026-08-03T06:42:09.193983Z","submitted_at":"2026-05-08T11:59:13Z","title":"Inference Time Causal Probing in LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-11T01:52:57.771365Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.07631"},"observation_digest":"sha256:14b6d94aae92d3e05129741dcca9b00c0b6ab1be7f38389f02175c19cedd5235","observation_id":"0c20fcae-52ae-4243-ae84-728ac04c1614","resolution":{"observed_at":"2026-05-11T04:15:56.655829Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-05-14T20:53:40.666929Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:30894512db96e9123102af104d936469bb7591760da5f49bf26d395668bf86b4","observation_id":"cb3374a0-800c-41f3-8d19-c044c05e6271","resolution":{"observed_at":"2026-05-14T20:59:28.728191Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":2},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-05-15T04:59:11.877068Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:2c42583347f18a978a2f60440758b805fa68c2ee199f4492964125deb4c8248a","observation_id":"5c7fa756-dd6a-45b9-a9c2-b8724b815aa8","resolution":{"observed_at":"2026-05-15T04:59:45.198036Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.17187","last_updated":"2026-05-16T22:52:11Z","snapshot_observed_at":"2026-07-06T23:28:12.114488Z","submitted_at":"2026-05-16T22:52:11Z","title":"PluRule: A Benchmark for Moderating Pluralistic Communities on Social Media","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-05-20T14:05:14.737146Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.17187"},"observation_digest":"sha256:9dfd89cd5036b2f0af11cea68311adcc514209840471a21e07d54c17464f0d7c","observation_id":"fc2a5594-641a-427c-b683-63fc7f3df93e","resolution":{"observed_at":"2026-05-20T14:08:20.663365Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2605.30076","last_updated":"2026-05-28T15:23:29Z","snapshot_observed_at":"2026-08-08T06:01:53.256304Z","submitted_at":"2026-05-28T15:23:29Z","title":"UniSteer: Text-Guided Flow Matching in Activation Space for Versatile LLM Steering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-29T08:06:57.884950Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2605.30076"},"observation_digest":"sha256:943e9985fba0219377491ee5917819fc9d3c671d8316806c86bf55cd1d03bdce","observation_id":"b08f1d97-8894-4303-a109-d45ba183695b","resolution":{"observed_at":"2026-06-29T08:13:15.605647Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2606.06902","last_updated":"2026-06-05T04:34:50Z","snapshot_observed_at":"2026-08-05T23:42:40.217026Z","submitted_at":"2026-06-05T04:34:50Z","title":"TALAN: Task-Aligned Latent Adaptation Networks for Targeted Post-Training of Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T22:18:34.218251Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2606.06902"},"observation_digest":"sha256:d7903042686c4ac65f508d6cf547c718a10016512df63b5a76c32029c1341656","observation_id":"48d25e09-f278-4ff2-91ce-580b690d697c","resolution":{"observed_at":"2026-07-02T16:57:09.506874Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2606.10929","last_updated":"2026-06-09T14:38:26Z","snapshot_observed_at":"2026-07-06T23:50:06.645076Z","submitted_at":"2026-06-09T14:38:26Z","title":"Recoverable but Not Stationary:Local Linear Structures in Weights and Activations","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T13:51:39.893972Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2606.10929"},"observation_digest":"sha256:e2c3617da769312a9c854bfedc8256a8dc456c68b496a6395c396c1106d8dd26","observation_id":"4658143a-772f-46c5-b9ff-9245bb3baa82","resolution":{"observed_at":"2026-07-03T04:27:37.336572Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2606.12234","last_updated":"2026-06-10T15:42:15Z","snapshot_observed_at":"2026-08-05T00:08:40.346158Z","submitted_at":"2026-06-10T15:42:15Z","title":"On The Effectiveness-Fluency Trade-Off In LLM Conditioning: A Systematic Study","version":1},"reference_index":174,"source":"arxiv_source","source_observed_at":"2026-06-27T09:40:48.736006Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2606.12234"},"observation_digest":"sha256:23b302a5781d66f82e860d469564cce73afc7615b0fd4004b0e568c0ac42f617","observation_id":"e71fa202-761b-4de3-b1fa-a7c697829c80","resolution":{"observed_at":"2026-07-03T11:08:03.476896Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2606.18389","last_updated":"2026-06-16T18:34:21Z","snapshot_observed_at":"2026-08-05T12:39:23.330047Z","submitted_at":"2026-06-16T18:34:21Z","title":"Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-06-27T00:46:36.000415Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2606.18389"},"observation_digest":"sha256:e43ea505f66bb7e93995586e63fa4874bef8928b4cc3a473e757a752482da62f","observation_id":"432f68ed-c554-47ca-a30d-6bb703f08691","resolution":{"observed_at":"2026-07-03T21:18:58.529050Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":"2404.03592","doi":"10.48550/arxiv.2404.03592","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reft: Representation finetuning for language models","venue":"arXiv (Cornell University)","work_id":"3018cc0e-7de7-4778-821b-7a75704527e0","year":2024},"citing_paper":{"arxiv_id":"2606.26396","last_updated":"2026-06-24T21:26:43Z","snapshot_observed_at":"2026-08-02T16:34:16.438122Z","submitted_at":"2026-06-24T21:26:43Z","title":"At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-06-26T01:27:39.812228Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2606.26396"},"observation_digest":"sha256:d8bbae2029c88cc292d5020b24ad77410423cb8692bfbf54acf737216c3eae76","observation_id":"1cd1b8be-1d1c-400a-acff-4036c7720e23","resolution":{"observed_at":"2026-06-26T01:28:50.549829Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:22.02325+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-01T19:55:53.978071Z","title":"Manning, and Christopher Potts","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16821","last_updated":"2026-07-18T13:43:44Z","snapshot_observed_at":"2026-08-07T16:44:16.045474Z","submitted_at":"2026-07-18T13:43:44Z","title":"First-Order Predictable but Pairwise Fragile: Local Task Adaptation in Trained Transformers","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-01T19:55:53.978071Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2607.16821"},"observation_digest":"sha256:37ab264efde6f38f0924db35695d3da92a16e0241b5f7a0030588c88f581f2fe","observation_id":"6754ccb3-32e8-4bdd-b205-a39ebf0180d0","resolution":{"observed_at":"2026-08-01T19:55:53.978071Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03592","snapshot_observed_at":"2026-08-01T06:04:46.122584Z","title":"and Potts, Christopher , month = may, year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22024","last_updated":"2026-07-24T06:43:09Z","snapshot_observed_at":"2026-08-08T12:54:01.031419Z","submitted_at":"2026-07-24T06:43:09Z","title":"Agent Security Needs Redefinition through a Holistic Framework","version":1},"reference_index":167,"source":"arxiv_source","source_observed_at":"2026-08-01T06:04:46.122584Z"},"links":{"cited_paper":"/paper/2404.03592","citing_paper":"/paper/2607.22024"},"observation_digest":"sha256:c50c3ef0a59c03cb4443c13426a7088fd8fcc7ec1835704f862c64fc68e784ca","observation_id":"fa4c3e9d-849a-446e-8262-dce7edfed99f","resolution":{"observed_at":"2026-08-01T06:04:46.122584Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.03592/citation-record","integrity":"/paper/2404.03592/integrity","json":"/paper/2404.03592/citation-record.json","paper":"/paper/2404.03592"},"outbound":[],"paper":{"arxiv_id":"2404.03592","last_updated":"2024-05-22T17:52:31Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:55:44.838732Z","submitted_at":"2024-04-04T17:00:37Z","title":"ReFT: Representation Finetuning for Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 31 inbound Pith citation observations for arXiv:2404.03592."}