{"as_of":"2026-08-08T04:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e095fd15b044de9c58b79ef115968f3a04f7280e75ca2d76b3dba14a3f0c4f61","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-14T19:56:06.762156Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T17:03:13.686066Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.12913","snapshot_observed_at":"2026-07-11T17:03:13.686066Z","title":"arXiv preprint arXiv:2605.12913 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04574","last_updated":"2026-07-06T01:02:30Z","snapshot_observed_at":"2026-08-07T10:27:24.643931Z","submitted_at":"2026-07-06T01:02:30Z","title":"A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-11T17:03:13.686066Z"},"links":{"cited_paper":"/paper/2605.12913","citing_paper":"/paper/2607.04574"},"observation_digest":"sha256:79c07f3445e587836a7978d3bfb8ac27688faef696d971ae1c936647ef2e88cf","observation_id":"02d6f244-0343-4cbd-a70c-83666b5ff433","resolution":{"observed_at":"2026-07-11T17:03:13.686066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2605.12913/citation-record","integrity":"/paper/2605.12913/integrity","json":"/paper/2605.12913/citation-record.json","paper":"/paper/2605.12913"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":"2303.08774","doi":"10.1002/tea.20265","metadata_source":"pith","pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4 Technical Report","venue":"cs.CL","work_id":"b928e041-6991-4c08-8c81-0359e4097c7b","year":2023},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:49186298e25a67aca883bfde7547aa8e0aeacc2f9af4a7cbf1860bbce372799d","observation_id":"0f338167-c8d8-4dfb-8361-fcc3fd9d278f","resolution":{"observed_at":"2026-05-14T19:57:53.211035Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T04:14:30.522565Z","title":"On-policy distillation of language models: Learning from self-generated mistakes","venue":null,"work_id":"3733ff2d-cd95-4776-9fa9-1b2328326749","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:912ad1826502b5d900aaf16a449c1ac00222df728e3660bbc2162b4121962763","observation_id":"0c3d0106-9ea7-4a48-9a11-affce4ab7d5a","resolution":{"observed_at":"2026-05-15T17:21:21.976243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dream: Deep research evaluation with agentic metrics","venue":null,"work_id":"8010f1a4-ea3c-4f11-8c31-857e66722934","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:9d39bea287b7d476747d3d8e1f40b42b4a5dd14ba5dc9edf23f2b84e0540291b","observation_id":"619dbdc9-3520-4728-8829-7cdc3964311c","resolution":{"observed_at":"2026-05-14T19:57:53.187522Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2505.20411","doi":"10.48550/arxiv.2505.20411","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents","venue":"ArXiv.org","work_id":"c819f5fe-32b6-41d1-aeb5-2d80c6fa8474","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:043137ad2ee560b7b39b3032e440a3b5aad03494dbb8addca4a8e2c17cab6d10","observation_id":"cc2818dd-c3f1-4f69-9690-043a094e1c59","resolution":{"observed_at":"2026-05-14T19:57:53.174612Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:50:48.545398+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:50:48.545398+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2603.00729","last_updated":"2026-02-28T16:25:04Z","snapshot_observed_at":"2026-07-06T22:47:24.369805Z","submitted_at":"2026-02-28T16:25:04Z","title":"Qwen3-Coder-Next Technical Report","version":1},"cited_work":{"arxiv_id":"2603.00729","doi":"10.48550/arxiv.2603.00729","metadata_source":"pith","pith_arxiv_id":"2603.00729","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen3-Coder-Next Technical Report","venue":"cs.CL","work_id":"ad966e68-641d-4b33-a9da-57cf741f35a6","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2603.00729","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:b137808f1802204d6346606e5829f2f357c5ac45617ac82bf4a8754c729fc1dd","observation_id":"06f21fcf-7552-41a3-9693-578dfdeeec95","resolution":{"observed_at":"2026-05-16T21:12:48.468873Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.16108","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T21:28:58.506549Z","title":"arXiv preprint arXiv:2511.16108(2025)","venue":null,"work_id":"cd691b36-09ff-4fda-9a35-a206d861e133","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:ffea90de58b32b2091ee6f5632c253a304c0f8a6e30c14778a898a01aab96c45","observation_id":"da6d06d9-ae7e-4996-af0d-a2e2c1138b09","resolution":{"observed_at":"2026-05-14T19:57:53.202579Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2602.02660","last_updated":"2026-05-19T23:41:59Z","snapshot_observed_at":"2026-08-01T13:24:46.487351Z","submitted_at":"2026-02-02T19:00:03Z","title":"MARS: Modular Agent with Reflective Search for Automated AI Research","version":3},"cited_work":{"arxiv_id":"2602.02660","doi":"10.48550/arxiv.2602.02660","metadata_source":"pith","pith_arxiv_id":"2602.02660","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mars: Modular agent with reflective search for automated ai research","venue":"cs.AI","work_id":"3a5d790e-9f71-42f7-a792-178ca85ca193","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2602.02660","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:3aba8f419f27812400c474d528ba68441e25acc610b336aed85ae4985264c3f5","observation_id":"c23039ba-560c-4e0e-ba44-696fcf0d6fbf","resolution":{"observed_at":"2026-05-21T02:04:10.539767Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12952","last_updated":"2025-03-03T02:27:02Z","snapshot_observed_at":"2026-08-07T16:15:45.210579Z","submitted_at":"2024-10-16T18:40:26Z","title":"Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning","version":2},"cited_work":{"arxiv_id":"2410.12952","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12952","snapshot_observed_at":"2026-07-01T13:55:46.371921Z","title":"Facilitating multi-turn function calling for llms via compositional instruction tuning","venue":null,"work_id":"6c5542cb-0f99-4d92-85f4-f7b97cd42104","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2410.12952","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:4694a8e71880bedc48061bbc43000841d4f7258e2ece17d585e33f616a1d373b","observation_id":"b534405e-cd85-4345-be75-717472ff255e","resolution":{"observed_at":"2026-05-14T19:57:53.313781Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.06600","last_updated":"2025-08-08T17:55:11Z","snapshot_observed_at":"2026-08-07T04:31:29.392346Z","submitted_at":"2025-08-08T17:55:11Z","title":"BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent","version":1},"cited_work":{"arxiv_id":"2508.06600","doi":"10.48550/arxiv.2508.06600","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.06600","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Browsecomp-plus: A more fair and transparent evaluation benchmark of deep-research agent","venue":"ArXiv.org","work_id":"699faba3-20e8-450a-9c1e-3cb57eb88807","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2508.06600","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:11abc1e745430786c35aaa250665821f8b4355762f402557b5818da52b70624b","observation_id":"1f76ec03-8ca9-4350-9d84-e9bd18427348","resolution":{"observed_at":"2026-05-14T19:57:53.390539Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01489","last_updated":"2024-10-29T17:29:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-01T17:24:45Z","title":"Agentless: Demystifying LLM-based Software Engineering Agents","version":2},"cited_work":{"arxiv_id":"2407.01489","doi":"10.48550/arxiv.2407.01489","metadata_source":"pith","pith_arxiv_id":"2407.01489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Agentless: Demystifying LLM-based Software Engineering Agents","venue":"cs.SE","work_id":"71c901c4-3c83-4e10-af54-3daef7fff397","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2407.01489","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:39b3788e0c297e76c490697f9145585eec0844cdeb5f8fa0c8201920b76a7f16","observation_id":"daeeb332-a50a-4ef3-a9f2-b377543fed49","resolution":{"observed_at":"2026-05-14T19:57:53.362813Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:50:51.153796+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:50:51.153796+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.06261","last_updated":"2025-12-19T14:25:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-07T17:36:04Z","title":"Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities","version":6},"cited_work":{"arxiv_id":"2507.06261","doi":"10.48550/arxiv.2503.19","metadata_source":"pith","pith_arxiv_id":"2507.06261","snapshot_observed_at":"2026-07-11T03:17:51.364436Z","title":"Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities","venue":"cs.CL","work_id":"008df105-2fdd-45d8-857a-8e35868aecb6","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2507.06261","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:7569a2a8a4531813a85ff2bcaa697b6229b6abc8720ce40f73487c8a3a7ec179","observation_id":"cb211981-c4ba-45fc-8e1c-144680c49ffb","resolution":{"observed_at":"2026-05-14T19:57:53.410083Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.16941","last_updated":"2025-11-14T22:00:03Z","snapshot_observed_at":"2026-08-06T21:34:46.041153Z","submitted_at":"2025-09-21T06:28:17Z","title":"SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?","version":2},"cited_work":{"arxiv_id":"2509.16941","doi":"10.48550/arxiv.2509.16941","metadata_source":"pith","pith_arxiv_id":"2509.16941","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?","venue":"cs.SE","work_id":"a561c78a-4b02-4053-a92a-bc5c7c5f6b9b","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2509.16941","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:db2edda1e2b07f2e312e3c197f84309e21067d5dee138f6fbd90f94b25a35191","observation_id":"c8ade44b-5959-4279-a90b-bffac6b7c730","resolution":{"observed_at":"2026-05-14T19:57:53.403116Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:50:48.977196+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:50:48.977196+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"MiniLLM: Knowledge distillation of large language models","venue":null,"work_id":"67f9e3f0-a6b1-4687-a666-21901460b114","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:c759127f485498be068f46df3498758c34a60fadcd499f24645c0220342032e6","observation_id":"9eb666c0-c41c-4e52-a503-419ec1963c9b","resolution":{"observed_at":"2026-05-15T17:21:22.023639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.17746","last_updated":"2025-10-03T01:55:55Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-23T17:57:55Z","title":"Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains","version":2},"cited_work":{"arxiv_id":"2507.17746","doi":"10.48550/arxiv.2507.17746","metadata_source":"pith","pith_arxiv_id":"2507.17746","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains","venue":"cs.LG","work_id":"805a846c-dae9-4375-abd8-a86dc6934496","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2507.17746","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:cddb38ed36197ded9c2b8ece5fdac126b5bb0d7285a8ceba4cb8b46141dfed88","observation_id":"0b8c2506-8401-4135-98f3-dcec997c47c8","resolution":{"observed_at":"2026-05-14T19:57:53.451850Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-23T21:53:02.879284+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T21:53:02.879284+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14196","last_updated":"2024-01-26T09:23:11Z","snapshot_observed_at":"2026-08-06T22:40:28.707813Z","submitted_at":"2024-01-25T14:17:53Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","version":2},"cited_work":{"arxiv_id":"2401.14196","doi":"10.48550/arxiv.2401.14196","metadata_source":"pith","pith_arxiv_id":"2401.14196","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","venue":"cs.SE","work_id":"f22dae5a-27e2-41d0-a061-c4286418dee3","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2401.14196","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:452b00c540782d1f9e0456b973ea82a8d6f15d8c2e51072939886eaa16623b66","observation_id":"aa436afe-a220-430c-b5b5-4fcee276890c","resolution":{"observed_at":"2026-05-14T19:57:53.320219Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-11T06:20:38.664414+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T06:20:38.664414+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models for software engineering: A systematic literature review.ACM Transactions on Software Engineering and Methodology, 33(8):1–79","venue":null,"work_id":"db704d1a-01fd-4ebc-a502-648f1aafc77e","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:b1587ad1ab0dd3d61da4c9a711533f585021f60688034a7205547ac4a64667f2","observation_id":"0cf73e6a-ab19-4c72-9a70-c6dab9e847e9","resolution":{"observed_at":"2026-05-15T17:21:22.040932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.16335","last_updated":"2026-03-13T02:23:49Z","snapshot_observed_at":"2026-08-04T04:51:19.798134Z","submitted_at":"2026-03-13T02:23:49Z","title":"Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents","version":1},"cited_work":{"arxiv_id":"2604.16335","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.16335","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents","venue":"cs.LG","work_id":"537adc3c-7056-4ae8-a90d-3206cb32e79c","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2604.16335","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:c939b845fb49fdcea168c036049300c1ed754d461d82a6e4e650f83d81a12c1f","observation_id":"4b40848d-8da1-4381-8ad0-214d3ede2699","resolution":{"observed_at":"2026-05-14T19:57:53.272134Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.20802","last_updated":"2026-02-16T14:49:34Z","snapshot_observed_at":"2026-07-29T19:52:32.104228Z","submitted_at":"2026-01-28T17:45:12Z","title":"Reinforcement Learning via Self-Distillation","version":2},"cited_work":{"arxiv_id":"2601.20802","doi":"10.48550/arxiv.2601.20802","metadata_source":"pith","pith_arxiv_id":"2601.20802","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reinforcement Learning via Self-Distillation","venue":"cs.LG","work_id":"b193541d-5853-4ea4-8e4b-8e4c08617eb6","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2601.20802","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:a6d8cae89837a91a09b012a01359fbb3162ad46b1c427e288c7ac86853c94968","observation_id":"59767a69-7b2b-4992-b20a-9e1d77c95c1f","resolution":{"observed_at":"2026-05-14T19:57:53.445431Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-21T06:23:12.649775+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T06:23:12.649775+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06770","last_updated":"2024-11-11T23:05:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T16:47:29Z","title":"SWE-bench: Can Language Models Resolve Real-World GitHub Issues?","version":3},"cited_work":{"arxiv_id":"2310.06770","doi":"10.1145/512927.512945","metadata_source":"pith","pith_arxiv_id":"2310.06770","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-bench: Can Language Models Resolve Real-World GitHub Issues?","venue":"cs.CL","work_id":"d0effe15-a689-441a-8e3f-ea35f1c4e4b1","year":2023},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2310.06770","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:b4e9b1e463231f812ad29d236e08804fc07b773ad6844e35799f6d8891d1dccd","observation_id":"9561e11b-83d9-4b19-b87d-8b9f31164a68","resolution":{"observed_at":"2026-05-14T19:57:53.298149Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.14895","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T00:29:16.233442Z","title":"arXiv preprint arXiv:2512.14895 , year=","venue":null,"work_id":"0e4c97e3-c655-45ae-b13e-28d6a6a415f7","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:de142a46aa9d7decee1f70dfafd86132df37bcddf646a9b50e3e5998f34d71ac","observation_id":"d76b8ae0-45fe-4b66-90ca-308bec072607","resolution":{"observed_at":"2026-05-14T19:57:53.194309Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02977","last_updated":"2025-12-03T03:33:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-04T15:59:41Z","title":"Large Language Model-Based Agents for Software Engineering: A Survey","version":2},"cited_work":{"arxiv_id":"2409.02977","doi":"10.48550/arxiv.2409.02977","metadata_source":"pith","pith_arxiv_id":"2409.02977","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Large Language Model-Based Agents for Software Engineering: A Survey","venue":"cs.SE","work_id":"65bf4f26-a45c-4639-841f-9f865ef1030e","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2409.02977","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:3fac8d77359cd1fd808b09d30ecee3dc67ce2c4a09e4c2d0cdb2203f09199511","observation_id":"260ee51f-7f7e-4ddd-b54b-6bd8aeabb2c5","resolution":{"observed_at":"2026-05-17T12:35:49.024248Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.64434/tml.20251026","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T16:57:24.393084Z","title":"On-policy distillation.Thinking Machines Lab: Con- nectionism","venue":null,"work_id":"bb76b11f-d59b-421e-88c6-fa0920ed09c3","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:945a4c0d151d2026cdef1978d08afa7b79a334fc93b2f9a8537b7d12dc9376b4","observation_id":"e9f924e2-7439-4608-9e75-431e6ff848a7","resolution":{"observed_at":"2026-05-14T19:57:52.351707Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-01T07:08:02.609025+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T07:08:02.609025+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T18:16:26.555721Z","title":"Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744","venue":null,"work_id":"aa3e2ba7-4265-495b-8612-615b2ddc9991","year":2022},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:7fe626a0367b36e5192e15079cbe9895f89d84d8611783fffcbb3c5b89ee215d","observation_id":"e3560fa6-2074-4060-b82b-87525a5b83d9","resolution":{"observed_at":"2026-05-15T17:21:22.027042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.21139","last_updated":"2025-06-06T07:53:20Z","snapshot_observed_at":"2026-07-06T20:14:49.976782Z","submitted_at":"2024-12-30T18:15:39Z","title":"Training Software Engineering Agents and Verifiers with SWE-Gym","version":2},"cited_work":{"arxiv_id":"2412.21139","doi":"10.48550/arxiv.2412.21139","metadata_source":"pith","pith_arxiv_id":"2412.21139","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Training Software Engineering Agents and Verifiers with SWE-Gym","venue":"cs.SE","work_id":"17189f19-7774-4b97-ab44-9966bf5d6d48","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2412.21139","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:30e749ad9029dcc393480c53b9e87a09a6314ad2e624a78da30b1e682770e10d","observation_id":"527fa34d-1bb3-4629-b3ef-1c8ec9fccfc7","resolution":{"observed_at":"2026-05-18T05:20:40.573423Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07782","last_updated":"2025-05-12T17:35:43Z","snapshot_observed_at":"2026-08-07T15:47:47.494462Z","submitted_at":"2025-05-12T17:35:43Z","title":"MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering","version":1},"cited_work":{"arxiv_id":"2505.07782","doi":"10.48550/arxiv.2505.07782","metadata_source":"arxiv_reference","pith_arxiv_id":"2505.07782","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qiang, Y","venue":"ArXiv.org","work_id":"ce9c3958-4ba9-4c15-b0ad-3d7398f95bb8","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2505.07782","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:320003af8d167f520512534ba6c179d03625f528def6012a1f90037d9261fa08","observation_id":"c4716b66-c20c-4d60-8e79-4fd9745cbe2a","resolution":{"observed_at":"2026-05-14T19:57:53.369729Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.07307","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mle-smith: Scaling mle tasks with automated multi-agent pipeline","venue":null,"work_id":"9431cf0a-65c6-4ba5-a904-f5e1f2f928f6","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:d84e03904247ea99943ca2ae1cf94ef1c7f0ed198dc9be9fefe65b46d184d8d9","observation_id":"7576f433-e031-40b6-9398-2cacf1c76b48","resolution":{"observed_at":"2026-05-14T19:57:53.291793Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficient reductions for imitation learning","venue":null,"work_id":"e62c9fd7-a55b-4c9f-b694-137e1ebf3765","year":2010},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:bbbcf1769c7add1f2ec578beec93628c53b07ee5db65219cbeb579fa52815c01","observation_id":"acf8cdbf-cc57-4916-b9d9-5dcbc17a9e7d","resolution":{"observed_at":"2026-05-15T17:21:22.030139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1406.5979","last_updated":"2014-06-23T17:00:28Z","snapshot_observed_at":"2026-07-06T03:47:05.007723Z","submitted_at":"2014-06-23T17:00:28Z","title":"Reinforcement and Imitation Learning via Interactive No-Regret Learning","version":1},"cited_work":{"arxiv_id":"1406.5979","doi":null,"metadata_source":"pith","pith_arxiv_id":"1406.5979","snapshot_observed_at":"2026-07-03T08:17:45.248813Z","title":"Reinforcement and Imitation Learning via Interactive No-Regret Learning","venue":"cs.LG","work_id":"7520e919-9fd9-44ca-8349-03a2f4b1fbcc","year":2014},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/1406.5979","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:105386e84a044a5bc9acb38696eb3150f68d7f729baa3b615c4b0b11e0a70d9e","observation_id":"3bf08f22-8d83-49dd-b4ca-e8470761cfcc","resolution":{"observed_at":"2026-05-14T19:57:53.264138Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A reduction of imitation learning and structured prediction to no-regret online learning","venue":null,"work_id":"2a670995-fbeb-4b29-b911-936163f35f7f","year":2011},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:e8c6f37707e220de6f2c27110cc79d8c3417a91a70fd60429a40bad0e51191de","observation_id":"5c454286-9ad8-45c8-9fc2-c8dcd10eaff8","resolution":{"observed_at":"2026-05-15T17:21:22.003131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":"1707.06347","doi":"10.1016/j.artint.2010.12.005","metadata_source":"pith","pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Proximal Policy Optimization Algorithms","venue":"cs.LG","work_id":"240c67fe-d14d-4520-91c1-38a4e272ca19","year":2017},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:563ba06a7417da754510752860cd02b13644f315e9fe5e678d0fba57b4c1cdb7","observation_id":"c16bdd4a-4ea6-4750-b0b3-029263b7e75c","resolution":{"observed_at":"2026-05-14T19:57:53.245712Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":"2402.03300","doi":"10.1016/0004-3702(73)90011-8","metadata_source":"pith","pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","venue":"cs.CL","work_id":"c5006563-f3ec-438a-9e35-b7b484f34828","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:6f594462fe8721ccad56801ac11b13c665d9aa0655c076683a1dfcfec3a90c04","observation_id":"36f185b7-b137-4671-bcb7-d0ea2bddae76","resolution":{"observed_at":"2026-05-14T19:57:53.439026Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Swe-dev: Building software engineering agents with training and inference scaling","venue":null,"work_id":"c5e89199-7280-44a6-bf84-434a128432b6","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:e1dae75b98d96c254960871cdbe2eaeec5ff40bdc404f4b6935e539b31a8283e","observation_id":"bd3ae417-308a-43ba-8ecd-d8b60f11a7b4","resolution":{"observed_at":"2026-05-15T17:21:22.007279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Software testing with large language models: Survey, landscape, and vision.IEEE Transactions on Software Engineering, 50(4):911–936","venue":null,"work_id":"452a677b-c0d5-41c7-acf7-54d1e559e54e","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:27852500c85d030f4d067698e1999a8422abe5a466b2454c072108ded886fe26","observation_id":"3bce33c8-dbd1-4780-8f1f-25c47ea3b937","resolution":{"observed_at":"2026-05-15T17:21:22.033420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16741","last_updated":"2025-04-18T18:14:31Z","snapshot_observed_at":"2026-08-02T14:58:44.167588Z","submitted_at":"2024-07-23T17:50:43Z","title":"OpenHands: An Open Platform for AI Software Developers as Generalist Agents","version":3},"cited_work":{"arxiv_id":"2407.16741","doi":"10.1145/3718958.3750537","metadata_source":"pith","pith_arxiv_id":"2407.16741","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"OpenHands: An Open Platform for AI Software Developers as Generalist Agents","venue":"cs.SE","work_id":"f1762ea0-e382-4f38-a28c-adc643789859","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2407.16741","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:124a4502044cb94527197a0bf9d0381e6efa6bdab1069030a65a155f05a8ff6f","observation_id":"517b65a0-f006-47e5-ba07-366f717446b7","resolution":{"observed_at":"2026-05-14T19:57:53.424827Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.12516","last_updated":"2025-04-16T22:27:45Z","snapshot_observed_at":"2026-08-03T00:43:33.338074Z","submitted_at":"2025-04-16T22:27:45Z","title":"BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents","version":1},"cited_work":{"arxiv_id":"2504.12516","doi":"10.48550/arxiv.2504.12516","metadata_source":"pith","pith_arxiv_id":"2504.12516","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents","venue":"cs.CL","work_id":"25adb508-d97c-49d6-ae43-7a70c2478a34","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2504.12516","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:bfa76cad063aef40c196493d1bcbd024c110bf1b582374a31a9d01072456d645","observation_id":"ebc54fea-072f-45f2-809c-f51714c706d3","resolution":{"observed_at":"2026-05-14T19:57:53.327350Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18449","last_updated":"2025-12-01T00:16:59Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-25T18:45:04Z","title":"SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution","version":2},"cited_work":{"arxiv_id":"2502.18449","doi":"10.48550/arxiv.2502.18449","metadata_source":"pith","pith_arxiv_id":"2502.18449","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution","venue":"cs.SE","work_id":"4b93fb93-87c9-40fe-84d0-d7ecb4e11bed","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2502.18449","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:d8ed27d5d66d4649b629ca1e75722c691df47f61382a0ab8954c136779534a47","observation_id":"f6306b97-77aa-429b-a27a-88fbaa638f72","resolution":{"observed_at":"2026-05-15T10:27:56.991478Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Automated program repair in the era of large pre-trained language models","venue":null,"work_id":"a45a222b-ddff-452e-a7bd-193208ec3703","year":2023},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:081c621e18bf0459435fb96c7ec49cfc8ff01e7dd82d850c552c9f02c73f7e8b","observation_id":"3c46f3c3-6578-4e08-87cc-4480fa49308b","resolution":{"observed_at":"2026-05-15T17:21:22.038515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":"2505.09388","doi":"10.1016/j.aiopen.2022.12","metadata_source":"pith","pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Qwen3 Technical Report","venue":"cs.CL","work_id":"25a4e30c-1232-48e7-9925-02fa12ba7c9e","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:34b93220e0ae6a3d99824836f7ce2f66e1ce01d28a6f08e2ea30f3f4ea7bf92f","observation_id":"6a7d32c6-f7fc-4d5d-8f47-1eff2b7a0f04","resolution":{"observed_at":"2026-05-14T19:57:53.235908Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T13:24:54.955583Z","title":"Swe-agent: Agent-computer interfaces enable automated software engineering.Advances in Neural Information Processing Systems, 37:50528–50652","venue":null,"work_id":"0621aa9d-3c5d-4171-ba59-3d6fb78d570d","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:b11f2d28685293ab1a5211ea4083fa999bac723890500630bf78ff9aa310e4ff","observation_id":"6bde1360-43e0-43e8-ad58-a28919fff1dc","resolution":{"observed_at":"2026-05-15T17:21:22.017613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.21798","last_updated":"2025-05-21T17:21:45Z","snapshot_observed_at":"2026-07-06T21:17:09.837496Z","submitted_at":"2025-04-30T16:56:06Z","title":"SWE-smith: Scaling Data for Software Engineering Agents","version":2},"cited_work":{"arxiv_id":"2504.21798","doi":"10.48550/arxiv.2504.21798","metadata_source":"pith","pith_arxiv_id":"2504.21798","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-smith: Scaling Data for Software Engineering Agents","venue":"cs.SE","work_id":"6a906763-2e4e-4cea-a19c-d7a169c9376b","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2504.21798","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:72796a46c3f13fcd22fb5c97c945771ea1661142de2fed301f6c14e1893e127f","observation_id":"9f97d393-789d-4cda-a4ec-5ba28789fa21","resolution":{"observed_at":"2026-05-15T10:22:07.061654Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01684","last_updated":"2025-09-01T18:04:10Z","snapshot_observed_at":"2026-08-07T23:18:57.894257Z","submitted_at":"2025-09-01T18:04:10Z","title":"Reinforcement Learning for Machine Learning Engineering Agents","version":1},"cited_work":{"arxiv_id":"2509.01684","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.01684","snapshot_observed_at":"2026-07-01T13:25:45.948001Z","title":"Reinforcement learning for machine learning engineering agents","venue":null,"work_id":"9bcd1420-adc0-4af1-b20b-f675b7fc5209","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2509.01684","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:fc3c1a5d22a46026bbe616bcb86ef9b92c0f5f399ab63ca6be4af85c8b64004b","observation_id":"83d2cc52-cd90-48ae-a519-dba65306dc3c","resolution":{"observed_at":"2026-05-14T19:57:53.418198Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.02333","last_updated":"2025-09-08T14:50:44Z","snapshot_observed_at":"2026-08-06T17:55:48.372585Z","submitted_at":"2025-09-02T14:01:07Z","title":"DCPO: Dynamic Clipping Policy Optimization","version":2},"cited_work":{"arxiv_id":"2509.02333","doi":"10.48550/arxiv.2509.02333","metadata_source":"pith","pith_arxiv_id":"2509.02333","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Dcpo: Dynamic clipping policy optimization","venue":"cs.CL","work_id":"8c19db85-51aa-4d83-8ade-6f3bc8d1c75e","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2509.02333","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:268924951b47911501581a6271ae7b281b9466e2397a65a939d5d50ecf36b795","observation_id":"a6d9ae2b-fa2d-4991-95a4-32a88213f45b","resolution":{"observed_at":"2026-05-14T19:57:53.349495Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.10778","last_updated":"2023-10-22T01:48:39Z","snapshot_observed_at":"2026-07-06T15:18:14.909173Z","submitted_at":"2023-04-21T07:08:26Z","title":"Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT","version":2},"cited_work":{"arxiv_id":"2304.10778","doi":"10.48550/arxiv.2304.10778","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.10778","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Evaluating the code quality of ai-assisted code generation tools: An empirical study on github copilot, amazon codewhisperer, and chatgpt","venue":"arXiv (Cornell University)","work_id":"fc34d942-a4d6-4670-b39a-c6c5537410cb","year":2023},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2304.10778","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:603790f5506674ea310eba1ef86d134abe63caefbba71532b4ae94a5f481075a","observation_id":"7160c5ee-8e62-4740-b672-920004c215c2","resolution":{"observed_at":"2026-05-14T19:57:53.334730Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14476","last_updated":"2025-05-20T01:37:34Z","snapshot_observed_at":"2026-08-02T01:40:54.187278Z","submitted_at":"2025-03-18T17:49:06Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","version":2},"cited_work":{"arxiv_id":"2503.14476","doi":"10.48550/arxiv.2503.14476","metadata_source":"pith","pith_arxiv_id":"2503.14476","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","venue":"cs.LG","work_id":"64019d00-0b11-4bbd-b173-b46c8fad0157","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2503.14476","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:b84e915561af29c11ade4220cc99cb343ca5cb09c06ecc1c80d3c39c06036209","observation_id":"da1863f4-b4ff-4fdf-9bf7-023c4ad3ac75","resolution":{"observed_at":"2026-05-14T19:57:53.356182Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-24T09:23:06.254602+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T09:23:06.254602+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.02605","last_updated":"2025-04-03T14:06:17Z","snapshot_observed_at":"2026-07-30T07:56:48.878578Z","submitted_at":"2025-04-03T14:06:17Z","title":"Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving","version":1},"cited_work":{"arxiv_id":"2504.02605","doi":"10.48550/arxiv.2504.02605","metadata_source":"pith","pith_arxiv_id":"2504.02605","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving","venue":"cs.SE","work_id":"c66ce635-0931-4807-8300-a45863330d75","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2504.02605","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:6701f89cab7ab5ba83aca3d498732ca30b1ce046ec8e79f328f2cf89ab84f316","observation_id":"16874846-5b3e-4a1d-a01b-1d0c9fd2a6ca","resolution":{"observed_at":"2026-05-16T06:48:50.578231Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:50:49.442994+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:50:49.442994+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2603.18815","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T17:08:43.027406Z","title":"type\": \"function","venue":null,"work_id":"5a21a37d-7198-4fa8-b16b-4210e37c3b65","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:d1470c417244707f42080913affb25ef09abd49a244be9de38d66d00e8485151","observation_id":"c02b3ea4-c9f0-4dd8-b92f-f1bd79cbaf88","resolution":{"observed_at":"2026-05-14T19:57:53.376666Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.07339","last_updated":"2024-08-09T06:16:55Z","snapshot_observed_at":"2026-07-06T17:15:22.551637Z","submitted_at":"2024-01-14T18:12:03Z","title":"CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges","version":2},"cited_work":{"arxiv_id":"2401.07339","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.07339","snapshot_observed_at":"2026-07-04T13:49:51.518818Z","title":"CodeAgent: Enhancing code generation with tool-integrated agent systems for real-world repo-level coding challenges","venue":null,"work_id":"6440eee2-590e-40c9-b4e9-bbd1004db03c","year":2024},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2401.07339","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:240e59f3089db209fb4ba30b8afbd076d4480bedd840d2d0398a6e3f1982b816","observation_id":"2a44fc95-3095-400e-9128-f119bb5dce30","resolution":{"observed_at":"2026-05-14T19:57:53.228204Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.18734","last_updated":"2026-03-20T15:40:19Z","snapshot_observed_at":"2026-08-07T20:24:25.671681Z","submitted_at":"2026-01-26T17:56:50Z","title":"Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models","version":3},"cited_work":{"arxiv_id":"2601.18734","doi":"10.18653/v1/2025.emnlp-main.125.https://aclanthology.org/2025.emnlp-main.125/","metadata_source":"pith","pith_arxiv_id":"2601.18734","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models","venue":"cs.LG","work_id":"bae00e84-9b0d-433d-a066-20b951f0b4d0","year":2026},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"cited_paper":"/paper/2601.18734","citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:bac3ee55ba1e53bb66a6c4e20c0bc240228fff1bd9168960827c668defc4c079","observation_id":"897e6c6e-d49a-4d09-a7bf-331fe64c42af","resolution":{"observed_at":"2026-05-14T19:57:53.432150Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.12216","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T10:58:02.936605Z","title":"why is X happening","venue":null,"work_id":"555951e3-27af-49cd-b613-0a8eb10754b0","year":2025},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:6d97be3c0615ccbedb32711f70dd94ab5ed30d53e64f2dda886593b3cf82ab86","observation_id":"70533bfb-237f-4ac6-8ece-62345060cbbb","resolution":{"observed_at":"2026-05-14T19:57:53.254003Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"1746a222-e117-4064-97f4-7e16a70e0d50","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:53ae3f57c104339ae64a0541fc34ae42dbf7446385ea5c954640e16d42a0776a","observation_id":"7dbd8c85-e67c-49f8-8fe5-35813f1bb9ba","resolution":{"observed_at":"2026-05-15T17:21:21.981784Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f5e0c818-43cb-4907-b778-68e2c926c36a","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:dfd55ff458e2f44fb8ec3e79b5520c78fc2196f11668a6eacbd63d3790418cf2","observation_id":"0ef470e4-df71-4411-a6b3-2c90ebfc3d28","resolution":{"observed_at":"2026-05-15T17:21:21.999657Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"* For new features: Consider test-driven development when appropriate","venue":null,"work_id":"0948d19c-14db-4c89-96cc-4ade9f55e0e7","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:4b9d25e56f963dcea7656600207f281dbcfc645388fd743cda9174c39493992f","observation_id":"3c6d5856-b5fe-4376-bba2-113e55cf9b85","resolution":{"observed_at":"2026-05-15T17:21:21.984473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"* Always modify existing files directly rather than creating new versions with different suffixes","venue":null,"work_id":"dc42baa9-0b9d-410d-a8a1-d16b7ec08f77","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:f3ac53af4f80842a156e6390d6fc6eeff5973ee343d8efdf9b5818f168cbea34","observation_id":"2f485735-736a-4d3c-bea6-e7866ff37ea8","resolution":{"observed_at":"2026-05-15T17:21:21.994555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"If the environment is not set up to run tests, consult with the user first before investing time to run tests","venue":null,"work_id":"44e3bf50-7e7f-4478-882e-a6f38abf66f4","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:f43e2485cb3b87e2996f4817c9c0227576bff5900327329aee44160db6166b7a","observation_id":"9aea05ad-2c89-44f0-9a11-da9e700f5985","resolution":{"observed_at":"2026-05-15T17:21:21.978756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d6e3376d-82db-4f58-8344-839fc3ea8ccb","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:c7d7e260687bce4ddadfe27035c63def40e189ebffef9c1676305ddccfe785e2","observation_id":"aeabb3c5-f9c5-40ee-8f7f-aa80a2375a39","resolution":{"observed_at":"2026-05-15T17:21:22.035833Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d4a189b1-59d2-41e0-a8b4-31c4af5a1888","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:fbe0851a8791c0e97531b06097b83947b9785ec514427cf4e9cec862966836a1","observation_id":"05a6a184-ed50-486e-ba9d-fb5a25a99587","resolution":{"observed_at":"2026-05-15T17:21:21.997213Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"* Similarly, if you encounter missing dependencies for essential tools requested by the user, install them when possible","venue":null,"work_id":"90888ecd-584a-4bcd-9e25-0ba1c096559d","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:ff544571d75ffa467ab7158e343e9504169ae1d7c49d68b2df48da5a41734c5a","observation_id":"f8b9512c-eb3a-4a4a-890f-1e144e86fbea","resolution":{"observed_at":"2026-05-15T17:21:22.010648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"dd9fe233-b844-4269-b133-215dd89b23e0","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:f210dc653f3eef250afb1aed49b1f28ba2c6c35122e6cb4a0e230deac87680aa","observation_id":"6981459f-cd26-40ba-aae3-c68def5a85fd","resolution":{"observed_at":"2026-05-15T17:21:22.020652Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"38507778-c528-48ee-b7a5-e311c3af22a2","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:c54c1547fbaefc85f6ca72c2939be16ea6b50bc6acb2c530cbbabfe3da7ba93e","observation_id":"98163856-8160-487c-a09e-45806d96673e","resolution":{"observed_at":"2026-05-15T17:21:21.988811Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"447e1f4e-ff7f-47cb-9412-494285036312","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:e3644bf1aa37bc04b001ed6a5da8c613698ec2ad9363a20090ff5152e515726f","observation_id":"13d66908-21cf-4e06-adc4-d96201bc8093","resolution":{"observed_at":"2026-05-15T17:21:21.991673Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"* When you run into any major issue while executing a plan from the user, please don’t try to directly work around it","venue":null,"work_id":"837bc914-cdd2-42af-8117-e9174d6dda9c","year":null},"citing_paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-14T19:56:06.762156Z"},"links":{"citing_paper":"/paper/2605.12913"},"observation_digest":"sha256:890facd4800c86776a3c3694d31a4efc6f10d5c853fe2842e7291e47ab7db108","observation_id":"b96d38d9-6fea-40ac-b09c-577ebd858a01","resolution":{"observed_at":"2026-05-15T17:21:22.014342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.12913","last_updated":"2026-05-13T02:40:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T02:40:28Z","title":"Revisiting DAgger in the Era of LLM-Agents"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":7,"verified_exact":36,"verified_fuzzy":15},"total_outbound_references":61},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2605.12913."}