{"as_of":"2026-08-21T23:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e4e316e77e5e27b5afc21b49235c3fbd6a9c6c2af6f13c280fd7c3050e60daa3","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":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":33,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:24:12.164371Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":1,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-16T11:24:12.164371Z","title":"A survey on post-training of large language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.15585","last_updated":"2025-06-09T02:36:20Z","snapshot_observed_at":"2026-08-17T21:55:02.668814Z","submitted_at":"2025-04-22T05:02:49Z","title":"A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment","version":4},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-16T11:24:12.164371Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2504.15585"},"observation_digest":"sha256:7f5a17d550599638b12546a5d0b86d8bef8469fe29654f5a06c2cd01f08bedb4","observation_id":"4d8180bf-c9a7-4835-ab8d-1e1323796074","resolution":{"observed_at":"2026-08-16T11:24:12.164371Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-16T05:41:31.003934Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.20024","last_updated":"2025-06-10T17:53:33Z","snapshot_observed_at":"2026-08-16T05:34:52.005177Z","submitted_at":"2025-04-28T17:48:43Z","title":"SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T05:41:31.003934Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2504.20024"},"observation_digest":"sha256:ec8fb8f90c3570649d63760dd1254baf711d22cba08e1bb4f7840500fa353c74","observation_id":"5c41d007-d776-4801-ab67-e3cb6d7bddcc","resolution":{"observed_at":"2026-08-16T05:41:31.003934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-15T20:37:48.237252Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.12457","last_updated":"2025-05-18T15:14:58Z","snapshot_observed_at":"2026-08-15T20:31:10.596175Z","submitted_at":"2025-05-18T15:14:58Z","title":"UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T20:37:48.237252Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2505.12457"},"observation_digest":"sha256:62c1c7367eb6af1a378088e93ec61554b208b82c690a9d83383a4963fa0d3bca","observation_id":"90576817-ff7f-49ce-ad8d-3f8dd5d8a6dc","resolution":{"observed_at":"2026-08-15T20:37:48.237252Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T14:49:48.412280Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17618","last_updated":"2025-05-23T08:25:46Z","snapshot_observed_at":"2026-08-13T12:52:39.280958Z","submitted_at":"2025-05-23T08:25:46Z","title":"Scaling Image and Video Generation via Test-Time Evolutionary Search","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T14:49:48.412280Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2505.17618"},"observation_digest":"sha256:d8701d921a89503053b5174eafa18aafd42dfb22bf91d825de5f0f0c95113486","observation_id":"2985e17c-62ae-4f72-b82f-ee393c0cc8da","resolution":{"observed_at":"2026-08-07T14:49:48.412280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T12:49:34.413285Z","title":"A survey on post-training of large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23450","last_updated":"2025-06-11T03:16:06Z","snapshot_observed_at":"2026-08-07T12:43:12.816737Z","submitted_at":"2025-05-29T13:56:49Z","title":"Agentic Robot: A Brain-Inspired Framework for Vision-Language-Action Models in Embodied Agents","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:49:34.413285Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2505.23450"},"observation_digest":"sha256:1984c5075ea3e62b246742e7fe9e177827ad01d93e9c5911ca0ba45dc4ac4373","observation_id":"749fe4ba-84ee-499d-b40c-a4addda8c2c6","resolution":{"observed_at":"2026-08-07T12:49:34.413285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T12:48:16.796706Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23561","last_updated":"2025-05-29T15:37:23Z","snapshot_observed_at":"2026-08-21T12:06:01.935071Z","submitted_at":"2025-05-29T15:37:23Z","title":"Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T12:48:16.796706Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2505.23561"},"observation_digest":"sha256:b3c465f193594aee9365dd5abc16848627c9a1c60855f1610fbd72a1bcaa1aae","observation_id":"bb41e4cd-3760-4d38-bda8-7dbc1c2cf741","resolution":{"observed_at":"2026-08-07T12:48:16.796706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T12:11:09.974387Z","title":"A survey on post-training of large language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.00309","last_updated":"2025-06-28T05:54:45Z","snapshot_observed_at":"2026-08-09T10:36:52.271268Z","submitted_at":"2025-05-30T23:37:37Z","title":"Evaluation of LLMs for mathematical problem solving","version":3},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-07T12:11:09.974387Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.00309"},"observation_digest":"sha256:efde8e1709b8ec628184d1a17ec31bbf5176087d2271366472a3cdb4f8ca251b","observation_id":"4e07f3b8-42ad-4c95-960f-c9b06133f978","resolution":{"observed_at":"2026-08-07T12:11:09.974387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T11:40:12.140220Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01748","last_updated":"2025-06-02T14:55:04Z","snapshot_observed_at":"2026-08-19T19:08:24.371118Z","submitted_at":"2025-06-02T14:55:04Z","title":"Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:40:12.140220Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.01748"},"observation_digest":"sha256:5d26cb50e21e2fcbd9349c2650e1d19f983254ae5367da4067b59924bcf411fb","observation_id":"8f259394-b12b-49e3-80cc-aafd09da5c70","resolution":{"observed_at":"2026-08-07T11:40:12.140220Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T11:21:40.383980Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.02726","last_updated":"2025-06-03T10:36:38Z","snapshot_observed_at":"2026-08-10T14:38:31.928986Z","submitted_at":"2025-06-03T10:36:38Z","title":"RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:21:40.383980Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.02726"},"observation_digest":"sha256:2971d3c185c3b4f9881b1e0494e5bff48079d98b18ab1c9689123de791d84ea1","observation_id":"fa508398-e9cd-4894-bbe0-055d2e765f73","resolution":{"observed_at":"2026-08-07T11:21:40.383980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T10:45:00.442702Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.04567","last_updated":"2025-06-05T02:37:10Z","snapshot_observed_at":"2026-08-15T17:07:34.068138Z","submitted_at":"2025-06-05T02:37:10Z","title":"StatsMerging: Statistics-Guided Model Merging via Task-Specific Teacher Distillation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T10:45:00.442702Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.04567"},"observation_digest":"sha256:64ebbaaf5cea39b8615ec89b0e331505738ed731ba71a76d1e0304cb29efb230","observation_id":"5ba99d04-4eaa-4223-bd5f-f6e1e04022ab","resolution":{"observed_at":"2026-08-07T10:45:00.442702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T10:42:41.050774Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.04611","last_updated":"2025-06-05T04:02:17Z","snapshot_observed_at":"2026-08-09T14:45:17.460081Z","submitted_at":"2025-06-05T04:02:17Z","title":"Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-07T10:42:41.050774Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.04611"},"observation_digest":"sha256:3ac7acc8576ece99a54d9231e2849c20d8966e1d6227255b381f02aa5ce9b5e8","observation_id":"34e36404-aa2b-42b4-a444-4a6c8b13f947","resolution":{"observed_at":"2026-08-07T10:42:41.050774Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-07T00:32:36.669532Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13666","last_updated":"2025-06-16T16:24:31Z","snapshot_observed_at":"2026-08-07T00:25:36.770856Z","submitted_at":"2025-06-16T16:24:31Z","title":"We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T00:32:36.669532Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2506.13666"},"observation_digest":"sha256:21f02f25727d7bac9f45a1b97b3b9529a7707899d392a1d6fe71180bf861a43d","observation_id":"f034a09e-e2fa-4274-ab49-808463f0e4b1","resolution":{"observed_at":"2026-08-07T00:32:36.669532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2507.19090","last_updated":"2026-04-03T15:54:21Z","snapshot_observed_at":"2026-07-06T22:02:41.705380Z","submitted_at":"2025-07-25T09:19:25Z","title":"Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents","version":4},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-19T02:52:18.207343Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2507.19090"},"observation_digest":"sha256:351594f559be6b1dedb92d6abff5bb1ac299806dedf696721eeecbc6e8913e5e","observation_id":"344e74b7-6b6d-4ac5-b00e-f46ed77ed415","resolution":{"observed_at":"2026-05-19T02:52:56.578307Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2507.21545","last_updated":"2026-04-20T08:38:38Z","snapshot_observed_at":"2026-08-14T15:00:59.399258Z","submitted_at":"2025-07-29T07:20:49Z","title":"UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-19T03:00:28.619627Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2507.21545"},"observation_digest":"sha256:809931e06e96b271dfb94f73549d6a8722831d8dea7844bbc7eaee3758723438","observation_id":"382a2fc7-5f2b-49d9-b335-a77c54885048","resolution":{"observed_at":"2026-05-19T03:02:00.195093Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2603.06610","last_updated":"2026-05-22T08:27:37Z","snapshot_observed_at":"2026-08-19T05:05:54.748868Z","submitted_at":"2026-02-19T09:46:24Z","title":"CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-25T06:40:51.046965Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2603.06610"},"observation_digest":"sha256:d656110608c7d469fd5f59baa0426e1c5081e6efb5c69e745244088c9d51fdf0","observation_id":"0913d030-05ef-494d-9f47-54c58ddeba2e","resolution":{"observed_at":"2026-05-25T06:45:26.381683Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2603.06610","last_updated":"2026-05-22T08:27:37Z","snapshot_observed_at":"2026-08-19T05:05:54.748868Z","submitted_at":"2026-02-19T09:46:24Z","title":"CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-25T06:40:51.046965Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2603.06610"},"observation_digest":"sha256:9fa30a30e3cbed9a951d917201c5562f4c05dfa769e9adb109d3a80731e01efc","observation_id":"2200eae5-6411-4a75-924c-f094d4b5c763","resolution":{"observed_at":"2026-05-25T06:45:25.616198Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.05091","last_updated":"2026-04-06T18:43:56Z","snapshot_observed_at":"2026-08-14T02:45:31.820007Z","submitted_at":"2026-04-06T18:43:56Z","title":"MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T18:57:25.256574Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.05091"},"observation_digest":"sha256:12604ecc5a934689da707ef9f3fb39efaade5c44798151034be10e25b21a53ea","observation_id":"f8152e74-e4a1-4d65-b15a-50b72014997f","resolution":{"observed_at":"2026-05-10T23:40:51.686523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.07941","last_updated":"2026-04-16T04:43:04Z","snapshot_observed_at":"2026-08-18T22:27:59.369562Z","submitted_at":"2026-04-09T08:00:37Z","title":"Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T18:28:58.515666Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.07941"},"observation_digest":"sha256:12474b5b6068ef40ca70bfcffabf9a5d17671afe2ed05a42e59809ff32734a06","observation_id":"1a496589-1f1e-4d66-ba05-cf69e8e7ef29","resolution":{"observed_at":"2026-05-11T00:30:53.473040Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.15306","last_updated":"2026-04-16T17:59:43Z","snapshot_observed_at":"2026-08-16T04:12:19.606812Z","submitted_at":"2026-04-16T17:59:43Z","title":"Generalization in LLM Problem Solving: The Case of the Shortest Path","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-10T10:37:45.355872Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.15306"},"observation_digest":"sha256:1d544bc90c4ea818767eb8e39feda8fdd161f419706d95f27103e0e8c2951088","observation_id":"9e770bc3-738e-4d8b-a5c6-5308cc17a77c","resolution":{"observed_at":"2026-05-10T10:39:38.183056Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.17384","last_updated":"2026-04-19T11:18:03Z","snapshot_observed_at":"2026-08-14T23:13:02.286205Z","submitted_at":"2026-04-19T11:18:03Z","title":"Towards a Data-Parameter Correspondence for LLMs: A Preliminary Discussion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T06:08:29.034434Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.17384"},"observation_digest":"sha256:6e493a48160e2453246179946f24a0d63103058ad189c457965b65d10ae7e7a6","observation_id":"36efc82d-2d95-4097-8bdb-5b428fcc64a3","resolution":{"observed_at":"2026-05-10T06:11:20.329052Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.27859","last_updated":"2026-05-15T06:25:17Z","snapshot_observed_at":"2026-08-15T01:50:12.462125Z","submitted_at":"2026-04-30T13:43:25Z","title":"Rethinking Agentic Reinforcement Learning In Large Language Models","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-07T06:30:09.945371Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.27859"},"observation_digest":"sha256:8588da244637d4d19e23eb9691ea95a7dfa79b54c16192b7a728e8926e3ce2e0","observation_id":"4c9a9789-2f93-4942-9757-da5d066e8402","resolution":{"observed_at":"2026-05-12T10:21:30.072630Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.27859","last_updated":"2026-05-15T06:25:17Z","snapshot_observed_at":"2026-08-15T01:50:12.462125Z","submitted_at":"2026-04-30T13:43:25Z","title":"Rethinking Agentic Reinforcement Learning In Large Language Models","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-08T03:12:19.414358Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.27859"},"observation_digest":"sha256:7d0caa23b893ae6ccb4e74be549482a35c7636d551b13d00750d96f45ab4e7c6","observation_id":"3505cd60-a493-4cbd-a313-2372364b0cc9","resolution":{"observed_at":"2026-05-11T22:11:17.120852Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2604.27859","last_updated":"2026-05-15T06:25:17Z","snapshot_observed_at":"2026-08-15T01:50:12.462125Z","submitted_at":"2026-04-30T13:43:25Z","title":"Rethinking Agentic Reinforcement Learning In Large Language Models","version":3},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-19T16:58:41.558250Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2604.27859"},"observation_digest":"sha256:ead32b1a49b33190d4fd40b6640351dc36a71e2e3f9ba97270dcc7429ec12970","observation_id":"f1668062-bcbe-4694-8b1f-6088aee1eda1","resolution":{"observed_at":"2026-05-19T17:02:40.755092Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2605.07105","last_updated":"2026-05-08T01:32:22Z","snapshot_observed_at":"2026-07-06T23:19:30.387067Z","submitted_at":"2026-05-08T01:32:22Z","title":"Theoretical Limits of Language Model Alignment","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:37.614335Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2605.07105"},"observation_digest":"sha256:3ed2545f0b13faaabfb3e60f34bd611849c39c71ad4655a24e5f3d8ce42634a2","observation_id":"9aa2dfce-41db-485e-b939-ab9ecc64a18b","resolution":{"observed_at":"2026-05-11T04:30:56.932350Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2605.08378","last_updated":"2026-05-08T18:36:25Z","snapshot_observed_at":"2026-08-16T09:49:54.305056Z","submitted_at":"2026-05-08T18:36:25Z","title":"Reinforcement Learning for Scalable and Trustworthy Intelligent Systems","version":1},"reference_index":198,"source":"pdf_text","source_observed_at":"2026-05-12T01:47:40.772146Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2605.08378"},"observation_digest":"sha256:0e85f949b6c0843428fc5c0fb9fd0116a7669bb05ac955b6349adafc61820ed5","observation_id":"7eaf3570-1433-45cc-bb52-90f1dded0cd6","resolution":{"observed_at":"2026-05-12T07:51:39.504015Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2605.11011","last_updated":"2026-05-10T11:05:20Z","snapshot_observed_at":"2026-08-14T17:25:04.017156Z","submitted_at":"2026-05-10T11:05:20Z","title":"LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-13T07:21:04.820743Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2605.11011"},"observation_digest":"sha256:0e88057d10b25efb763280bfa5e94cf51b3499e3cf7601b29c39dbca23db4d3f","observation_id":"baa8338e-4d8c-4e59-b001-0520fc461a9e","resolution":{"observed_at":"2026-05-13T07:22:28.687150Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2605.25326","last_updated":"2026-05-25T01:16:19Z","snapshot_observed_at":"2026-08-12T21:19:04.030063Z","submitted_at":"2026-05-25T01:16:19Z","title":"Perceive-then-Plan: Layout-as-Policy for Monocular 3D Scene Layout Estimation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-29T23:11:59.282627Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2605.25326"},"observation_digest":"sha256:27aaac4cdb97ff29dbcc3258d3fa4fddf15e5869b882dba5b98fc074aad33d55","observation_id":"9e42d6c9-8b0d-4a5d-8a9f-e162057c0f33","resolution":{"observed_at":"2026-06-29T23:14:01.326606Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2606.02313","last_updated":"2026-06-01T14:31:35Z","snapshot_observed_at":"2026-08-06T08:39:50.187649Z","submitted_at":"2026-06-01T14:31:35Z","title":"Towards Precise Intent-Aligned VLA Aerial Navigation via Expert-Guided GRPO","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T14:28:23.759920Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2606.02313"},"observation_digest":"sha256:13c547a1c81309e04135e859eecadf4bd393b6960441568060f451b20941d6f4","observation_id":"4e1e8bb6-a282-49be-84c9-eccaaa97a374","resolution":{"observed_at":"2026-07-01T23:16:24.741003Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2606.19744","last_updated":"2026-06-18T03:20:41Z","snapshot_observed_at":"2026-08-13T04:45:55.638519Z","submitted_at":"2026-06-18T03:20:41Z","title":"Beyond Uniform Forgetting: A Study of Sequential Direct Preference Optimization Across Preference Settings","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-06-26T18:02:52.726302Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2606.19744"},"observation_digest":"sha256:77722c5b2545cda3212a20392c6b8a251e1e3cf3ed00d80964655bc6bb60711b","observation_id":"10242a74-1712-47ef-ba48-c1b4056cc28b","resolution":{"observed_at":"2026-07-04T03:29:29.878076Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2606.24428","last_updated":"2026-06-23T11:05:05Z","snapshot_observed_at":"2026-08-18T19:29:51.757015Z","submitted_at":"2026-06-23T11:05:05Z","title":"Escaping the Self-Confirmation Trap: An Execute-Distill-Verify Paradigm for Agentic Experience Learning","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-06-25T23:49:38.932474Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2606.24428"},"observation_digest":"sha256:488a60b0df527ce86fa113efe581b7d24e15afe4f02958686d9f0aea9eac28f1","observation_id":"de8bfa77-b442-4afc-b43c-f4255e2bad24","resolution":{"observed_at":"2026-07-04T17:20:00.112152Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2606.27136","last_updated":"2026-06-25T15:11:02Z","snapshot_observed_at":"2026-08-14T10:46:02.142005Z","submitted_at":"2026-06-25T15:11:02Z","title":"Joint Learning of Experiential Rules and Policies for Large Language Model Agents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-26T04:33:27.112576Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2606.27136"},"observation_digest":"sha256:e3e9505bf3a2e9e5389d6839855d8d65a80fd57c012ba22c7c0de46664c2fd80","observation_id":"66091e5b-96d4-4368-84cf-fc0c4e4e9527","resolution":{"observed_at":"2026-07-04T14:09:52.567243Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":"2503.06072","doi":"10.48550/arxiv.2503.06072","metadata_source":"pith","pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"press/v274/thede25a.html","venue":"cs.CL","work_id":"9da1f966-0b72-4212-add9-795e0232302e","year":2025},"citing_paper":{"arxiv_id":"2607.06004","last_updated":"2026-07-07T08:46:49Z","snapshot_observed_at":"2026-08-07T20:54:25.112855Z","submitted_at":"2026-07-07T08:46:49Z","title":"Large Language Models Have Unreliable Understanding of Software Engineering Terminology","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-08T20:22:54.983733Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2607.06004"},"observation_digest":"sha256:e542e673da4dd72ec87172424372985a98209feef5b454d4ff73c8da720c734d","observation_id":"9afe6952-51de-40dd-8f4c-db80729f7bce","resolution":{"observed_at":"2026-07-08T20:25:37.271473Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06072","snapshot_observed_at":"2026-08-01T10:22:41.523534Z","title":"A survey on post-training of large language models.arXiv preprint arXiv:2503.06072, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20286","last_updated":"2026-07-22T15:31:28Z","snapshot_observed_at":"2026-08-13T15:23:40.531295Z","submitted_at":"2026-07-22T15:31:28Z","title":"Sound Probabilistic Safety Bounds for Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T10:22:41.523534Z"},"links":{"cited_paper":"/paper/2503.06072","citing_paper":"/paper/2607.20286"},"observation_digest":"sha256:29ef0a104c3990899ce2082cb84d153557a8f37192279788497947a598e73f9b","observation_id":"6c04f95a-7dec-4c72-858d-3d7ac5584f24","resolution":{"observed_at":"2026-08-01T10:22:41.523534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.06072/citation-record","integrity":"/paper/2503.06072/integrity","json":"/paper/2503.06072/citation-record.json","paper":"/paper/2503.06072"},"outbound":[],"paper":{"arxiv_id":"2503.06072","last_updated":"2025-08-01T01:52:05Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T12:51:59.712632Z","submitted_at":"2025-03-08T05:41:42Z","title":"A Survey on Post-training of Large 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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2503.06072."}