{"as_of":"2026-08-06T03:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:672be47b8548c862a0160c884abb019dba19cc3b89337d30c1cd8e37dda0777c","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-16T23:26:04.445225Z","state":"measured"},{"denominator":94,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":94,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":81,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":81,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T22:10:17.623600Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":9,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2310.02170","last_updated":"2024-11-15T04:30:04Z","snapshot_observed_at":"2026-07-06T16:27:11.151651Z","submitted_at":"2023-10-03T16:05:48Z","title":"A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-21T21:05:25.809179Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2310.02170"},"observation_digest":"sha256:0a17e32f35cc8e2b244cdb2d0573955318b07da444b02539df861216583ecae2","observation_id":"12de5b60-320e-4a15-87cb-e42af6c1d278","resolution":{"observed_at":"2026-05-21T21:05:25.955179Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2310.11511","last_updated":"2023-10-17T18:18:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-17T18:18:32Z","title":"Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-05-12T14:15:10.907921Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2310.11511"},"observation_digest":"sha256:c1240c0d0e55a9caad94b9c8c42a5a73f23eb472b392fbe30876840edfbc2daf","observation_id":"dc54b941-7eea-4ff6-a017-bca4ad0fbc9b","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2404.11584","last_updated":"2024-04-17T17:32:41Z","snapshot_observed_at":"2026-08-04T23:37:27.678120Z","submitted_at":"2024-04-17T17:32:41Z","title":"The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-16T23:16:41.679855Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2404.11584"},"observation_digest":"sha256:2b0f3a3efd035c8adc3be05d35e035b2ef9cf01838328b1f82d8a1b0bc29a7a0","observation_id":"2af3bda2-817b-44a4-b74f-941c5c1fbf83","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2504.01990","last_updated":"2025-08-02T12:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-31T18:00:29Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","version":2},"reference_index":215,"source":"pdf_text","source_observed_at":"2026-05-22T21:39:49.832151Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2504.01990"},"observation_digest":"sha256:be2c39eec65e123ae21a5d3cf539fd168b33484c964c766edd02f1dc9e400782","observation_id":"0d7665e1-4c19-4e90-b932-3c055abcb908","resolution":{"observed_at":"2026-05-22T21:42:10.706564Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2504.19678","last_updated":"2026-03-06T19:01:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-28T11:08:22Z","title":"From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-15T02:57:37.873567Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2504.19678"},"observation_digest":"sha256:e73d564c8b8e0e405fdb61e7179196f18947c734e2b78be4e336709d808fbabe","observation_id":"9588357b-563e-47ad-9a9c-e8e3196b5a7d","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2505.11737","last_updated":"2026-04-11T18:08:02Z","snapshot_observed_at":"2026-08-02T07:06:47.956538Z","submitted_at":"2025-05-16T22:47:32Z","title":"TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning","version":4},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-22T13:58:07.913104Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2505.11737"},"observation_digest":"sha256:02dd85603c0e5e32a0acd9aab2c0339909e6ea92133117587753965e15de8f9b","observation_id":"1e660460-f535-4684-94e5-3f0020baae39","resolution":{"observed_at":"2026-05-22T14:01:38.246330Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T22:09:46.514342Z","title":"Language agent tree search unifies reasoning acting and planning in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07434","last_updated":"2025-08-10T17:11:56Z","snapshot_observed_at":"2026-08-05T22:09:44.745603Z","submitted_at":"2025-08-10T17:11:56Z","title":"Let's Revise Step-by-Step: A Unified Local Search Framework for Code Generation with LLMs","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-05T22:09:46.514342Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2508.07434"},"observation_digest":"sha256:5e2bb5242a008bfd16f336ea2073b1b34479e7ebe8200389a8426fc07c91e8b4","observation_id":"78515099-a3ab-4044-832b-423e53ada154","resolution":{"observed_at":"2026-08-05T22:09:46.514342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T22:10:17.623600Z","title":", Yan, K","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07571","last_updated":"2025-08-19T11:54:07Z","snapshot_observed_at":"2026-08-05T22:10:14.525356Z","submitted_at":"2025-08-11T03:05:36Z","title":"Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-05T22:10:17.623600Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2508.07571"},"observation_digest":"sha256:ce1a8d8cb8b9409dcb43a24449052c9ad938a24645fd9f235ec1d84b9e9b198f","observation_id":"05c88c66-2fff-4c1d-a197-66f3648179c5","resolution":{"observed_at":"2026-08-05T22:10:17.623600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-04T21:27:36.485905Z","title":"Language agent tree search unifies reasoning acting and planning in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.07680","last_updated":"2025-09-09T17:59:39Z","snapshot_observed_at":"2026-08-04T21:27:30.632810Z","submitted_at":"2025-09-09T17:59:39Z","title":"CAViAR: Critic-Augmented Video Agentic Reasoning","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-04T21:27:36.485905Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2509.07680"},"observation_digest":"sha256:c8e6f1a13dd231d361389d8bf85e39c9a1ac087f509f06f038411744c29090b0","observation_id":"f0aa01ba-00b7-4a5d-83f6-8b028f9903ae","resolution":{"observed_at":"2026-08-04T21:27:36.485905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2510.08804","last_updated":"2026-05-04T16:48:58Z","snapshot_observed_at":"2026-08-02T08:04:43.071958Z","submitted_at":"2025-10-09T20:35:23Z","title":"MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-18T08:28:59.161675Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2510.08804"},"observation_digest":"sha256:94e1b0fd97293a364a061182c5c3890af7d84128ec8c011a13a5213dd7b86237","observation_id":"e7eca22c-3472-46a5-81df-00b9850a40f9","resolution":{"observed_at":"2026-05-18T08:31:06.881386Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2510.14703","last_updated":"2026-04-28T18:17:43Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-10-16T14:06:03Z","title":"ToolPRM: Fine-Grained Inference Scaling of Structured Outputs for Function Calling","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-18T06:30:39.858246Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2510.14703"},"observation_digest":"sha256:098c4ad374014d326c5d884be73161294d16bf29d3efb48f9b59beb75527a542","observation_id":"251c1f51-7dfa-47e9-9dd1-cf90f0b7df5d","resolution":{"observed_at":"2026-05-18T06:30:59.550154Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2511.00739","last_updated":"2026-04-16T18:23:56Z","snapshot_observed_at":"2026-08-03T23:57:10.965977Z","submitted_at":"2025-11-01T23:46:44Z","title":"Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-18T00:55:14.213746Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2511.00739"},"observation_digest":"sha256:a0c1b224435aafdd152c40053f18fcd4087e36328ebe92d7acbbe4fccb13fe99","observation_id":"351e0a36-4ee0-4821-80d1-4593320cff88","resolution":{"observed_at":"2026-05-18T00:55:33.455392Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2512.18470","last_updated":"2026-04-04T09:52:04Z","snapshot_observed_at":"2026-07-30T13:30:43.108201Z","submitted_at":"2025-12-20T19:08:15Z","title":"SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios","version":5},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-05-16T20:24:40.939455Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2512.18470"},"observation_digest":"sha256:b56b9baa0248c83e7fd6bf2b4014064f3728fc47fb4ac7d7f1d89dccadd14c1e","observation_id":"0d845924-2cbc-4d81-8570-96cf5d1ddfd9","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T13:15:17.364127Z","title":"Language agent tree search unifies reasoning acting and planning in language models.arXiv preprint arXiv:2310.04406, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.25065","last_updated":"2026-06-16T17:27:56Z","snapshot_observed_at":"2026-08-03T13:15:16.027112Z","submitted_at":"2025-12-31T18:58:19Z","title":"Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Search","version":2},"reference_index":122,"source":"pdf_text","source_observed_at":"2026-08-03T13:15:17.364127Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2512.25065"},"observation_digest":"sha256:b05c642b7c65ae78f232443189211a4608e6dfca3de58667879cd5c036f881e1","observation_id":"102b5759-5ee6-464c-9ef1-18e2ad77f893","resolution":{"observed_at":"2026-08-03T13:15:17.364127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T12:30:24.914356Z","title":"Language agent tree search unifies reasoning, acting, and planning in language models.arXiv preprint arXiv:2310.04406, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02880","last_updated":"2026-06-08T07:25:41Z","snapshot_observed_at":"2026-08-04T14:55:36.857899Z","submitted_at":"2026-01-06T10:05:30Z","title":"ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T12:30:24.914356Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2601.02880"},"observation_digest":"sha256:838b93f43b3bd0b201109838ac05a37e536173ae6483d37b3cf0be9de8dff588","observation_id":"eaa71471-1034-4bb9-877c-5556c61901b9","resolution":{"observed_at":"2026-08-03T12:30:24.914356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T09:21:51.102294Z","title":"Language agent tree search unifies reasoning acting and planning in language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.14192","last_updated":"2026-07-03T11:26:58Z","snapshot_observed_at":"2026-08-03T09:21:30.130466Z","submitted_at":"2026-01-20T17:51:56Z","title":"Toward Efficient Agents: Memory, Tool learning, and Planning","version":2},"reference_index":200,"source":"pdf_text","source_observed_at":"2026-08-03T09:21:51.102294Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2601.14192"},"observation_digest":"sha256:856d55932aa3f810feb06dd42198ad285d2de6165d6bceee4818eb993f926a9b","observation_id":"73f41000-7a78-413a-bcce-daf28c1e72ba","resolution":{"observed_at":"2026-08-03T09:21:51.102294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T03:30:06.655664Z","title":"Language agent tree search unifies reasoning acting and planning in language models.arXiv preprint arXiv:2310.04406, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.07883","last_updated":"2026-05-31T12:48:43Z","snapshot_observed_at":"2026-08-03T08:00:00.664050Z","submitted_at":"2026-02-08T09:27:18Z","title":"ToolSelf: Unifying Task Execution and Self-Reconfiguration via Tool-Driven Emergent Adaptation","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T03:30:06.655664Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2602.07883"},"observation_digest":"sha256:4638dcfcf726c97e27f44e5004dc91adea33afc26b57d5806a2482ba2639ac8f","observation_id":"63ad2063-9751-4054-9169-9ccc34c0bdc9","resolution":{"observed_at":"2026-08-03T03:30:06.655664Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T22:58:14.002340Z","title":"Language agent tree search unifies reasoning acting and planning in language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.15382","last_updated":"2026-05-28T08:46:27Z","snapshot_observed_at":"2026-08-03T23:19:36.572742Z","submitted_at":"2026-02-17T06:31:53Z","title":"The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems","version":2},"reference_index":103,"source":"arxiv_source","source_observed_at":"2026-08-02T22:58:14.002340Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2602.15382"},"observation_digest":"sha256:35271e22fd921fb8cf5e34b1db17ff4b34cbac42ba2bf8d682563dab9a8984de","observation_id":"35e2b54b-ccc1-4386-8685-8c8934fd467d","resolution":{"observed_at":"2026-08-02T22:58:14.002340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2602.20867","last_updated":"2026-02-24T13:11:38Z","snapshot_observed_at":"2026-07-29T17:42:23.433838Z","submitted_at":"2026-02-24T13:11:38Z","title":"SoK: Agentic Skills -- Beyond Tool Use in LLM Agents","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-14T23:19:31.024268Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2602.20867"},"observation_digest":"sha256:a60b4cccbb5073d320646a3ae4e5512f59a7edf120031f628575a55226efd8ab","observation_id":"27c9762d-b4f3-40d7-9185-b44999ac3f3e","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T20:41:12.143511Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.22638","last_updated":"2026-06-10T08:57:04Z","snapshot_observed_at":"2026-08-02T20:41:07.202173Z","submitted_at":"2026-02-26T05:39:38Z","title":"MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T20:41:12.143511Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2602.22638"},"observation_digest":"sha256:31599a1c89d84c729c89bd0222f8bd75bb58f5bb9130400a6837cf283777c2b1","observation_id":"381b54b9-1094-4a00-bf71-5472d9f4d647","resolution":{"observed_at":"2026-08-02T20:41:12.143511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2604.06633","last_updated":"2026-04-08T03:18:51Z","snapshot_observed_at":"2026-07-06T22:55:06.424752Z","submitted_at":"2026-04-08T03:18:51Z","title":"Argus: Reorchestrating Static Analysis via a Multi-Agent Ensemble for Full-Chain Security Vulnerability Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T18:15:02.002711Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2604.06633"},"observation_digest":"sha256:3eebd917690e8e7540f9cbec409ec87f28f6fb71f5740484e654e3fadaa6878c","observation_id":"e3371784-3171-44d4-ae69-f533ac48659d","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2604.09308","last_updated":"2026-04-10T13:16:44Z","snapshot_observed_at":"2026-07-06T22:58:12.847181Z","submitted_at":"2026-04-10T13:16:44Z","title":"Constraint-Aware Corrective Memory for Language-Based Drug Discovery Agents","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-10T16:36:48.946686Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2604.09308"},"observation_digest":"sha256:0b8dae6eaf7a7c71cdb66eb3116a162b3996c3eeab292761acac90c89e0619f4","observation_id":"e35e57af-a1f8-40c9-88d4-50d1c94cec5f","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2604.10449","last_updated":"2026-04-12T04:15:31Z","snapshot_observed_at":"2026-07-06T22:59:05.519456Z","submitted_at":"2026-04-12T04:15:31Z","title":"AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-05-10T16:35:16.056397Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2604.10449"},"observation_digest":"sha256:1ef0d23b23b6fd2295970e6815d3e8208c21a4b7577c2ef6f1e3da411a13a717","observation_id":"95249e38-6238-4350-ac50-b95c3fd6d6ac","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2604.10734","last_updated":"2026-04-12T17:14:36Z","snapshot_observed_at":"2026-07-06T22:59:18.756089Z","submitted_at":"2026-04-12T17:14:36Z","title":"Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T15:58:15.150613Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2604.10734"},"observation_digest":"sha256:cc3ad96184bb2e1caac7757eab38682f33de84640cc75753ef2cf52204e5fb00","observation_id":"b79ad8f1-6498-4659-96bc-12b51f1c09bb","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.03356","last_updated":"2026-05-05T04:29:38Z","snapshot_observed_at":"2026-08-06T03:15:11.788829Z","submitted_at":"2026-05-05T04:29:38Z","title":"POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition Inference","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-05-07T16:04:48.394294Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.03356"},"observation_digest":"sha256:70b3fee7315aadc7889a14fd49d3173a364b1b13eab8022591e9d1ae0b8ba057","observation_id":"d1bc6cdc-ce09-481e-b4fb-24e2e3d018cd","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.05701","last_updated":"2026-05-07T05:45:58Z","snapshot_observed_at":"2026-07-31T16:49:48.024454Z","submitted_at":"2026-05-07T05:45:58Z","title":"Inference-Time Budget Control for LLM Search Agents","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-08T11:51:02.872129Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.05701"},"observation_digest":"sha256:86b17bb1c6b1445f1fc76c17af28d9c15044ccfbe615c3dcbcfc01455bfc7f84","observation_id":"61df1bb9-1931-4108-9fe4-752bcec336aa","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.06365","last_updated":"2026-05-07T14:39:37Z","snapshot_observed_at":"2026-07-06T23:18:51.157048Z","submitted_at":"2026-05-07T14:39:37Z","title":"From Agent Loops to Deterministic Graphs: Execution Lineage for Reproducible AI-Native Work","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T09:50:30.639962Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.06365"},"observation_digest":"sha256:f481314fe525a7036f6ae6cd0dd053be594ad372365323f55089fc64d5050556","observation_id":"1845dd4a-ec78-4a9a-8503-fc4ac966e291","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-05-12T03:37:09.000442Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:cbe7b2ccd5a9c03adb94b9f8488dbd345b7630c6481754b9f1fc5ab519733b25","observation_id":"ff51167e-aeeb-440f-a6f6-db4192a31b2f","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-05-15T05:25:43.890367Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:770e7acc19e1ce36c638d0ebba94077d4fdbc43a73ed5a216707b31bed0e77ce","observation_id":"3a2bcdff-b67e-42f1-939e-3dd77ffd7c2a","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":3},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-05-20T22:12:23.680155Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:b6df3eb8513e6eaac885e89f8bb90c97f3a7c2b1b8a32bd578a1f169ca9db744","observation_id":"fa1b6f08-a9aa-4ae8-8caf-d14ee49f83b6","resolution":{"observed_at":"2026-05-20T22:13:47.003256Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.10913","last_updated":"2026-06-24T17:55:07Z","snapshot_observed_at":"2026-08-02T06:55:55.998448Z","submitted_at":"2026-05-11T17:50:51Z","title":"Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-12T03:29:33.497561Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.10913"},"observation_digest":"sha256:8bf933edd515d55ad4551776d7f9d1624f193ceae2115e1c95971171e886fca3","observation_id":"b3355c9d-4e4b-4ad5-b9a8-ae9d4ca8a7e3","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.10913","last_updated":"2026-06-24T17:55:07Z","snapshot_observed_at":"2026-08-02T06:55:55.998448Z","submitted_at":"2026-05-11T17:50:51Z","title":"Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-06-30T22:24:26.528532Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.10913"},"observation_digest":"sha256:e3261465a98ee2231b31562de624d4d263d7c7e333a47a20d3bfc6e687df571c","observation_id":"5c9e292e-0cde-41f2-9430-db34a9572b1e","resolution":{"observed_at":"2026-06-30T22:25:06.830807Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.11853","last_updated":"2026-05-14T10:19:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-12T09:38:38Z","title":"GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-13T06:44:30.069444Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.11853"},"observation_digest":"sha256:8abe9bd2d80245323acc241f5339ab8b09ee323d15fec045eb43e15e5998af18","observation_id":"3b9b421f-15e5-48a5-98bb-a4aac349a9a0","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.11853","last_updated":"2026-05-14T10:19:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-12T09:38:38Z","title":"GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-15T05:59:23.949124Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.11853"},"observation_digest":"sha256:93418377e4e246c4bb2ab3971965a7aef03df6012648b393dac88575b01196ec","observation_id":"464c56df-c6f9-452f-9fb8-0114957c076a","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.12087","last_updated":"2026-05-12T13:09:07Z","snapshot_observed_at":"2026-07-06T23:23:48.960874Z","submitted_at":"2026-05-12T13:09:07Z","title":"Intermediate Artifacts as First-Class Citizens: A Data Model for Durable Intermediate Artifacts in Agentic Systems","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T04:38:38.425043Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.12087"},"observation_digest":"sha256:7eac1427b37eeb0f205fc26e97d586d6220132d5dd3078e9c742f13db65a8241","observation_id":"e28f2a98-42df-4266-98f4-974fa17bd5ea","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.12755","last_updated":"2026-05-12T21:09:43Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:09:43Z","title":"State-Centric Decision Process","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-14T19:37:39.247986Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.12755"},"observation_digest":"sha256:33cf8dca0763ae1331d9e5f95154e4f815b360ca8a5dfd32444c8453bbfe597f","observation_id":"53741c5e-4427-4d1c-9bb3-3d8b0f2fe660","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.13625","last_updated":"2026-05-13T14:52:40Z","snapshot_observed_at":"2026-07-06T23:25:11.623026Z","submitted_at":"2026-05-13T14:52:40Z","title":"How to Interpret Agent Behavior","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-14T18:23:25.269217Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.13625"},"observation_digest":"sha256:4df4f3aead44f7ba12136facf2ddd0158243c9d3f30cb60bf3afc512ec0d16ef","observation_id":"c4d4ee95-ed39-4dce-87fb-afd6267bd280","resolution":{"observed_at":"2026-05-16T23:26:04.564922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.21516","last_updated":"2026-05-15T12:47:13Z","snapshot_observed_at":"2026-08-02T04:12:03.015112Z","submitted_at":"2026-05-15T12:47:13Z","title":"Harnesses for Inference-Time Alignment over Execution Trajectories","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-22T01:03:56.207217Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.21516"},"observation_digest":"sha256:5e0fe27ef1ac6b03288be752a537aeb0ebb19762040419d20798b62bfc5d284d","observation_id":"2f65eae0-9dde-4779-b27b-dbb91f0f294e","resolution":{"observed_at":"2026-05-22T01:04:31.922558Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.22106","last_updated":"2026-05-21T07:40:57Z","snapshot_observed_at":"2026-07-06T23:32:30.578213Z","submitted_at":"2026-05-21T07:40:57Z","title":"ArborKV: Structure-Aware KV Cache Management for Scaling Tree-based LLM Reasoning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-22T05:48:30.118982Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.22106"},"observation_digest":"sha256:17c34f52a8ad3cc5ff49d10e02aae6432f9ab6517b20754314803d3e4bbd6a58","observation_id":"6ed46c50-9189-46b6-ba47-e4e3633f19bd","resolution":{"observed_at":"2026-05-22T05:51:08.761831Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.22138","last_updated":"2026-05-21T08:11:54Z","snapshot_observed_at":"2026-07-06T23:32:30.578213Z","submitted_at":"2026-05-21T08:11:54Z","title":"Efficient Agentic Reasoning Through Self-Regulated Simulative Planning","version":1},"reference_index":127,"source":"pdf_text","source_observed_at":"2026-05-22T06:33:36.846345Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.22138"},"observation_digest":"sha256:dd69b9f2fdbba5d9c88f2f1bd990769943254cb7ee1e41869c27fbf66dcf205f","observation_id":"9699bf59-eb38-426c-9663-58adc7283ca9","resolution":{"observed_at":"2026-05-22T06:34:41.019850Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.22566","last_updated":"2026-05-21T14:45:40Z","snapshot_observed_at":"2026-07-30T13:51:09.634852Z","submitted_at":"2026-05-21T14:45:40Z","title":"GraphFlow: A Graph-Based Workflow Management for Efficient LLM-Agent Serving","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-22T07:18:27.003144Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.22566"},"observation_digest":"sha256:76a278f105013551d9e65bebb8266e54a7547bd6d2d8f1f4916d8161a24edc32","observation_id":"d519ebec-8283-44d3-aaf8-6defcb958333","resolution":{"observed_at":"2026-05-22T07:21:13.030333Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.23972","last_updated":"2026-05-13T12:55:34Z","snapshot_observed_at":"2026-08-01T12:03:41.594468Z","submitted_at":"2026-05-13T12:55:34Z","title":"Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-30T21:36:44.033596Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.23972"},"observation_digest":"sha256:aeca0f7292ea14ba8496ad5a2af3e5b56617d77d5a3fe2870e923a2352042462","observation_id":"5bd991a7-5f38-48af-9080-b8cbc1037254","resolution":{"observed_at":"2026-07-01T14:25:46.598515Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.25141","last_updated":"2026-05-24T15:40:55Z","snapshot_observed_at":"2026-07-06T23:35:06.733347Z","submitted_at":"2026-05-24T15:40:55Z","title":"LLM Agent Based Renewable Energy Forecasting Using Edge and IoT Data A Review of Solar Wind Weather and Grid Aware Decision Support","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-30T11:51:12.039968Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.25141"},"observation_digest":"sha256:61016fcbbf95c5a411d7b08674df4276baa8cb1f96bdb295eca49a27a2c2d826","observation_id":"936b9d1c-981e-4b96-bacc-2a5d8d79c54d","resolution":{"observed_at":"2026-06-30T11:54:38.262906Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.29463","last_updated":"2026-05-31T05:31:18Z","snapshot_observed_at":"2026-08-03T20:29:40.314314Z","submitted_at":"2026-05-28T06:56:42Z","title":"Honest Lying: Understanding Memory Confabulation in Reflexive Agents","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T09:17:49.904150Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.29463"},"observation_digest":"sha256:37baf3dd3a636d4d08da5aaed814f96add61da6a1e6ca2ee4dbd26108ea1fdf0","observation_id":"ba56935d-c49b-4d57-9e34-b9fdbf485b85","resolution":{"observed_at":"2026-06-29T09:23:16.536359Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.30052","last_updated":"2026-05-28T15:03:17Z","snapshot_observed_at":"2026-08-01T03:51:14.473875Z","submitted_at":"2026-05-28T15:03:17Z","title":"REPOT: Recoverable Program-of-Thought via Checkpoint Repair","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-06-29T06:22:46.440678Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.30052"},"observation_digest":"sha256:0832bfbe01fe085167ac755e2e85f97e25bf564815153f93586d2e894418c891","observation_id":"ce40e05b-1482-440c-b769-2f9dee79e693","resolution":{"observed_at":"2026-06-29T06:23:08.667776Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2605.31492","last_updated":"2026-05-29T16:13:19Z","snapshot_observed_at":"2026-08-04T03:12:04.713123Z","submitted_at":"2026-05-29T16:13:19Z","title":"LinTree: Improving LLM Reasoning with Explicitly Structured Search Histories","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-28T22:04:56.620892Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2605.31492"},"observation_digest":"sha256:13ea259acbdf8731f60a437ec61462a42b699a8d72b20a95cd6395fda8a25e27","observation_id":"f9cf76ba-9c94-457f-a339-d399f399acaa","resolution":{"observed_at":"2026-07-01T19:46:10.689189Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.06140","last_updated":"2026-06-04T13:19:53Z","snapshot_observed_at":"2026-07-06T23:46:01.165261Z","submitted_at":"2026-06-04T13:19:53Z","title":"RedEdit: Agentic Red-Teaming of Image Safety Classifiers via MCTS-Guided Photo-Editing","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-06-28T00:42:33.088388Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.06140"},"observation_digest":"sha256:be102d98fb84b4eecbe2561177879a6bc11b640ffc6bb662468e92e4ddd73d0c","observation_id":"643834e1-57f5-4592-80fa-07ae390457ff","resolution":{"observed_at":"2026-07-02T14:07:02.822459Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.07999","last_updated":"2026-06-06T06:33:51Z","snapshot_observed_at":"2026-08-01T19:10:51.691151Z","submitted_at":"2026-06-06T06:33:51Z","title":"Efficient Skill Grounding via Code Refactoring with Small Language Models","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-06-27T19:55:20.212198Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.07999"},"observation_digest":"sha256:ed8078842fffcc4392325cfbeb9e5dfa5a39c1b8bd9eddac1858128274852d6a","observation_id":"bfc93bdf-a764-4e4f-844b-63952706e6d6","resolution":{"observed_at":"2026-07-02T21:07:24.071443Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.08346","last_updated":"2026-06-06T21:29:01Z","snapshot_observed_at":"2026-08-04T04:08:00.245750Z","submitted_at":"2026-06-06T21:29:01Z","title":"CATPO: Critique-Augmented Tree Policy Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T19:30:07.971424Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.08346"},"observation_digest":"sha256:607587f382d8845575778b595105c777f929e2dbc08ca1fa752347c8137f3106","observation_id":"103d5440-53de-4723-b5ab-ab0e331a01eb","resolution":{"observed_at":"2026-07-02T21:47:28.022770Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.11119","last_updated":"2026-06-09T17:16:03Z","snapshot_observed_at":"2026-07-31T16:22:30.560541Z","submitted_at":"2026-06-09T17:16:03Z","title":"TRACE: A Unified Rollout Budget Allocation Framework for Efficient Agentic Reinforcement Learning","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-06-27T13:55:35.363377Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.11119"},"observation_digest":"sha256:e675f5dd83635e1e488c46c7e03febbaa9bcccc8dae8752c34f3dc6748bb6bb9","observation_id":"d644ab24-5af6-4d75-846d-7d9dae5b4753","resolution":{"observed_at":"2026-07-03T04:27:36.768106Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.11926","last_updated":"2026-06-10T10:57:05Z","snapshot_observed_at":"2026-07-06T23:50:53.469137Z","submitted_at":"2026-06-10T10:57:05Z","title":"Toward Generalist Autonomous Research via Hypothesis-Tree Refinement","version":1},"reference_index":170,"source":"arxiv_source","source_observed_at":"2026-06-27T09:34:41.800309Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.11926"},"observation_digest":"sha256:bf159394caea5555012a6cec7e6226112a0138cd4e0c7ab8117ae3638dbcac18","observation_id":"f66d517f-a3b5-46a8-ad24-8a98a309ded4","resolution":{"observed_at":"2026-06-27T09:40:47.033901Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.12384","last_updated":"2026-07-31T08:54:09Z","snapshot_observed_at":"2026-08-05T23:10:46.327902Z","submitted_at":"2026-06-10T17:47:07Z","title":"APPO: Agentic Procedural Policy Optimization","version":1},"reference_index":101,"source":"pdf_text","source_observed_at":"2026-06-27T10:21:55.485624Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.12384"},"observation_digest":"sha256:2b1e619c2f7f2d19d54735fc97f05c2feea848f748571c18d0e8041b80f8f90d","observation_id":"7375a646-25ff-4924-a91f-43f0313fa72c","resolution":{"observed_at":"2026-07-03T09:37:49.274018Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T02:12:35.829243Z","title":"calculate","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.12384","last_updated":"2026-07-31T08:54:09Z","snapshot_observed_at":"2026-08-05T23:10:46.327902Z","submitted_at":"2026-06-10T17:47:07Z","title":"APPO: Agentic Procedural Policy Optimization","version":2},"reference_index":101,"source":"pdf_text","source_observed_at":"2026-08-03T02:12:35.829243Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.12384"},"observation_digest":"sha256:f4a90c565524c090d4dfba67dea4b014607262acbd75ff238258c000458649f1","observation_id":"9d203ab2-fb43-4d08-bb93-740fed2ae9e9","resolution":{"observed_at":"2026-08-03T02:12:35.829243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.13097","last_updated":"2026-07-29T12:55:33Z","snapshot_observed_at":"2026-08-02T11:44:00.617729Z","submitted_at":"2026-06-11T09:25:27Z","title":"Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T05:26:48.431739Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.13097"},"observation_digest":"sha256:29c95ab0df1805fed57e09078a12b56653d558f4822fb9eeb3f4d1dadfdd8817","observation_id":"7517829c-f786-45c8-94cc-ef2a7e53930d","resolution":{"observed_at":"2026-06-27T05:30:35.757923Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T11:44:05.367701Z","title":"Language agent tree search unifies reasoning acting and planning in language models.arXiv preprint arXiv:2310.04406,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.13097","last_updated":"2026-07-29T12:55:33Z","snapshot_observed_at":"2026-08-02T11:44:00.617729Z","submitted_at":"2026-06-11T09:25:27Z","title":"Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T11:44:05.367701Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.13097"},"observation_digest":"sha256:7f3d5fd511bc6799e5d3f5b0d1669add963a469eecf83ce2d4f145acd6bde774","observation_id":"408dec40-0710-44a4-a884-c03ce45a1fe8","resolution":{"observed_at":"2026-08-02T11:44:05.367701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.21777","last_updated":"2026-06-19T21:50:35Z","snapshot_observed_at":"2026-07-06T23:56:45.447705Z","submitted_at":"2026-06-19T21:50:35Z","title":"CalVerT: Augmenting Agents with Calibrated Verifier Telemetry Improves Action and Learning in Knowledge-Intensive Tasks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-26T13:57:04.036806Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.21777"},"observation_digest":"sha256:b64129e0c854fa9411fac3c66a2b32d5f7103812704845089b91a5d2d9dd179d","observation_id":"c65a7088-a4c6-47b4-a708-84238797718d","resolution":{"observed_at":"2026-07-04T06:59:38.119939Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.24937","last_updated":"2026-07-27T15:17:17Z","snapshot_observed_at":"2026-08-02T23:19:25.465662Z","submitted_at":"2026-06-22T17:48:54Z","title":"The Hitchhiker's Guide to Agentic AI: From Foundations to Systems","version":1},"reference_index":239,"source":"pdf_text","source_observed_at":"2026-06-26T08:09:57.542558Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.24937"},"observation_digest":"sha256:1bf8087752676dddf1a782af36f7fd885317bfc5253768a741dd3063eeceb69f","observation_id":"b38096d2-7a70-4df2-bdf2-69b16bb94257","resolution":{"observed_at":"2026-07-04T11:09:46.464179Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T10:27:18.547412Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.24937","last_updated":"2026-07-27T15:17:17Z","snapshot_observed_at":"2026-08-02T23:19:25.465662Z","submitted_at":"2026-06-22T17:48:54Z","title":"The Hitchhiker's Guide to Agentic AI: From Foundations to Systems","version":2},"reference_index":225,"source":"pdf_text","source_observed_at":"2026-08-02T10:27:18.547412Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.24937"},"observation_digest":"sha256:e390d05a74e00ddf5d11fe0d9b698062e690b3d4e4931e3c58a75306ab8bcb74","observation_id":"6648cfe1-d04f-40e6-8b20-f49098a5652f","resolution":{"observed_at":"2026-08-02T10:27:18.547412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.25354","last_updated":"2026-06-29T23:57:32Z","snapshot_observed_at":"2026-07-06T23:59:47.542695Z","submitted_at":"2026-06-24T03:42:44Z","title":"Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-25T21:29:40.564852Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.25354"},"observation_digest":"sha256:64cc90f22de84edac107bbf8543d2491c02ea8e13e730e8c279b90fb21923543","observation_id":"8102495f-7fe9-4a53-8f19-ae68d79f92ca","resolution":{"observed_at":"2026-07-04T19:20:06.686209Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.25354","last_updated":"2026-06-29T23:57:32Z","snapshot_observed_at":"2026-07-06T23:59:47.542695Z","submitted_at":"2026-06-24T03:42:44Z","title":"Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-01T06:33:45.824727Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.25354"},"observation_digest":"sha256:114fdceea15366735f403cef24e4bed966530b67dfd98a6826da0f182081cb7c","observation_id":"fb5ec80d-5f1f-4302-af48-955d1c41b1bc","resolution":{"observed_at":"2026-07-01T06:35:29.575402Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.25705","last_updated":"2026-06-24T11:18:01Z","snapshot_observed_at":"2026-07-07T00:00:07.201776Z","submitted_at":"2026-06-24T11:18:01Z","title":"GUI agent: Guided Exploration of User-Sensitive Screens","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-25T20:34:05.239277Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.25705"},"observation_digest":"sha256:24bc3bc241b98b9c432e61adcf3b3cebd9e16881345e545b8f9742d15bf71172","observation_id":"0b6acd4a-930a-4ae8-9080-9b2c5a3099ea","resolution":{"observed_at":"2026-07-04T20:10:08.736824Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.26964","last_updated":"2026-06-26T09:10:44Z","snapshot_observed_at":"2026-08-05T10:39:41.227539Z","submitted_at":"2026-06-25T12:38:39Z","title":"Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-26T04:51:38.355857Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.26964"},"observation_digest":"sha256:e783b19d1f8e480a0821de6f00020796359920f8850369510d176440282772f5","observation_id":"9a7500ab-4dce-4411-a59f-c5b10ac2d08b","resolution":{"observed_at":"2026-07-04T13:49:52.334266Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.26964","last_updated":"2026-06-26T09:10:44Z","snapshot_observed_at":"2026-08-05T10:39:41.227539Z","submitted_at":"2026-06-25T12:38:39Z","title":"Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-29T04:55:32.982338Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.26964"},"observation_digest":"sha256:0865a3454c2e0a594b47bfe52544df77ec34019e647962f5f07c0bf9f8c0654a","observation_id":"27115395-2f45-42ef-b94f-d183daf60a2f","resolution":{"observed_at":"2026-06-29T19:13:52.836971Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.27806","last_updated":"2026-07-05T07:44:24Z","snapshot_observed_at":"2026-08-02T12:52:55.369851Z","submitted_at":"2026-06-26T07:45:15Z","title":"Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-06-29T04:46:11.090693Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.27806"},"observation_digest":"sha256:e4498e536937ca5529c1256b7eb2237822319af7ddb55cf53f030a47c0702805","observation_id":"967a4ce6-cbb6-478e-a9b7-3500cc81a051","resolution":{"observed_at":"2026-06-29T19:23:54.354974Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.27806","last_updated":"2026-07-05T07:44:24Z","snapshot_observed_at":"2026-08-02T12:52:55.369851Z","submitted_at":"2026-06-26T07:45:15Z","title":"Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-07-03T22:41:41.912274Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.27806"},"observation_digest":"sha256:4c82a3f953921e8e5d2a88291b5094ec1745eee900543bee2fbad007b1d9f6e0","observation_id":"b9e05298-bf36-491c-abce-fb3a8c6ec982","resolution":{"observed_at":"2026-07-03T22:49:01.165561Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2606.31422","last_updated":"2026-07-05T04:18:26Z","snapshot_observed_at":"2026-07-12T10:09:39.454479Z","submitted_at":"2026-06-30T09:45:49Z","title":"Ask the World Before Acting: Environment Probing for Calibrated Agent World Models","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-01T05:58:45.194034Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2606.31422"},"observation_digest":"sha256:66c0c76b7bbdaacc31ed00639f72c8fd2c558cc58bf7759dd3e3130faa747702","observation_id":"4615df0d-98cf-4c47-ba76-df3b93f9eb96","resolution":{"observed_at":"2026-07-01T09:55:41.568288Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2607.00038","last_updated":"2026-06-28T18:30:46Z","snapshot_observed_at":"2026-08-01T16:40:43.486088Z","submitted_at":"2026-06-28T18:30:46Z","title":"Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-02T20:40:11.059493Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.00038"},"observation_digest":"sha256:a545c43bc1626f1e2fe86d54614b83898d15d6aa02f260af164c2aaf382fa1be","observation_id":"c25b16cb-e0e5-407a-b541-7420009f3e55","resolution":{"observed_at":"2026-07-02T20:47:22.241543Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2607.01942","last_updated":"2026-07-02T09:34:20Z","snapshot_observed_at":"2026-07-07T00:07:28.231599Z","submitted_at":"2026-07-02T09:34:20Z","title":"Atomic Task Graph: A Unified Framework for Agentic Planning and Execution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-03T13:59:31.697155Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.01942"},"observation_digest":"sha256:521b297fe29f806c0430d7ac5e10e8f9c42325dfe6ca332d4e16387fe97c1a68","observation_id":"b8379c14-3aa3-4369-813b-857fba467c30","resolution":{"observed_at":"2026-07-03T14:08:21.524614Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-12T08:56:22.090660Z","title":"arXiv preprint arXiv:2310.04406 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02615","last_updated":"2026-07-08T18:37:12Z","snapshot_observed_at":"2026-07-12T23:17:37.962772Z","submitted_at":"2026-07-01T17:28:56Z","title":"TAG: A Lightweight Framework for Test-Driven Agentic Artifact Generation","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-12T08:56:22.090660Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.02615"},"observation_digest":"sha256:a2407e231a59c1e12add783aa5a543cbc8b9b5023ae0459f80ec503e0a60d771","observation_id":"6c8b7101-fb0e-43c9-8c69-80e7d442bb03","resolution":{"observed_at":"2026-07-12T08:56:22.090660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2607.05391","last_updated":"2026-07-07T17:26:37Z","snapshot_observed_at":"2026-08-06T03:00:58.001418Z","submitted_at":"2026-07-06T17:59:35Z","title":"LLM-as-a-Verifier: A General-Purpose Verification Framework","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-07T12:47:29.552283Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.05391"},"observation_digest":"sha256:f1500da15af62531e4db3fd2506960c606aaaead2be63fdc0bf5e45c2263a946","observation_id":"278a59a0-5571-42a3-be58-ee5f962599d4","resolution":{"observed_at":"2026-07-07T12:53:50.308171Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-11T07:02:51.850836Z","title":"Lan- guage agent tree search unifies reasoning acting and planning in language models.arXiv preprint arXiv:2310.04406, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.05391","last_updated":"2026-07-07T17:26:37Z","snapshot_observed_at":"2026-08-06T03:00:58.001418Z","submitted_at":"2026-07-06T17:59:35Z","title":"LLM-as-a-Verifier: A General-Purpose Verification Framework","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-11T07:02:51.850836Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.05391"},"observation_digest":"sha256:4112340c31c1c39354bfe7c8c5da5fa4ca29672a6daa04db6db037f0770e3b99","observation_id":"89204035-561d-4e1a-9817-6978bcb41109","resolution":{"observed_at":"2026-07-11T07:02:51.850836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":"2310.04406","doi":"10.48550/arxiv.2310.04406","metadata_source":"pith","pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":"cs.AI","work_id":"810dbb8b-e954-4797-bf0d-5d8cad94e524","year":2023},"citing_paper":{"arxiv_id":"2607.06764","last_updated":"2026-07-07T19:49:35Z","snapshot_observed_at":"2026-07-11T23:18:33.952091Z","submitted_at":"2026-07-07T19:49:35Z","title":"Cost-Effective Agent Harnesses for Abstract Reasoning and Generalization on ARC-AGI-1","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-10T21:50:04.193411Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.06764"},"observation_digest":"sha256:377115bbbd331ae692b74bef9e25b7b53760fb3857d46f5e40279814c9504e21","observation_id":"f81e6c2c-9095-47ea-b3bf-74cd93b20a78","resolution":{"observed_at":"2026-07-10T21:57:37.884622Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-13T05:59:23.238387Z","title":"arXiv preprint arXiv:2310.04406 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.08894","last_updated":"2026-07-09T19:34:29Z","snapshot_observed_at":"2026-07-15T23:17:56.360081Z","submitted_at":"2026-07-09T19:34:29Z","title":"GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-13T05:59:23.238387Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.08894"},"observation_digest":"sha256:d4105692d37303f2a8619a11cc4726486009df9a53fb37491bf94fb4be71f66b","observation_id":"c8caead3-e8df-46c5-8e50-99b362aa1201","resolution":{"observed_at":"2026-07-13T05:59:23.238387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-13T02:38:56.095095Z","title":"arXiv preprint arXiv:2310.04406 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.09493","last_updated":"2026-07-10T15:07:00Z","snapshot_observed_at":"2026-07-15T23:18:27.595194Z","submitted_at":"2026-07-10T15:07:00Z","title":"Shared Selective Persistent Memory for Agentic LLM Systems","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-13T02:38:56.095095Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.09493"},"observation_digest":"sha256:d791c89b6ce7fbd2c7a009521dd50d26858d297eeaf2598071d60d9a7ad465c8","observation_id":"bd4b90ba-acbb-4f01-8c35-c3264a40bcb3","resolution":{"observed_at":"2026-07-13T02:38:56.095095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T05:43:00.474045Z","title":"Language agent tree search unifies reasoning acting and planning in language models, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.14159","last_updated":"2026-07-14T21:22:18Z","snapshot_observed_at":"2026-08-03T18:33:58.376458Z","submitted_at":"2026-07-14T21:22:18Z","title":"MemoHarness: Agent Harnesses That Learn from Experience","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-02T05:43:00.474045Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.14159"},"observation_digest":"sha256:794c94259de64b4dd32f4b3d9ee106d6807c3abbb433e02c11641903af61519e","observation_id":"4203f7dc-1b1f-48bd-a63e-d1814d2cea87","resolution":{"observed_at":"2026-08-02T05:43:00.474045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-01T07:28:25.067620Z","title":"arXiv preprint arXiv:2310.04406 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21453","last_updated":"2026-07-24T02:14:44Z","snapshot_observed_at":"2026-08-03T14:01:50.133228Z","submitted_at":"2026-07-23T15:55:29Z","title":"Test-Time Scaling via Error Localization","version":2},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-01T07:28:25.067620Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.21453"},"observation_digest":"sha256:d60ba94f729777f167480dee915f3f87ad81ee623fd20c316d8b0f0cf3d8d624","observation_id":"c30be134-1909-4436-9278-6c48387d63b0","resolution":{"observed_at":"2026-08-01T07:28:25.067620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T12:39:58.810913Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22569","last_updated":"2026-06-01T04:20:25Z","snapshot_observed_at":"2026-08-05T23:45:32.394636Z","submitted_at":"2026-06-01T04:20:25Z","title":"Execution-Grounded Security Testing for Coding Agents in Software Engineering Pipelines","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T12:39:58.810913Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.22569"},"observation_digest":"sha256:4b8130427f307ea25ebe114c43c696196ecd5c7f266ad449518601342dec370f","observation_id":"d952d248-111c-4670-96a2-b20960082b61","resolution":{"observed_at":"2026-08-02T12:39:58.810913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-02T11:32:12.529986Z","title":"2024 , booktitle =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22602","last_updated":"2026-06-12T16:51:29Z","snapshot_observed_at":"2026-08-05T12:54:59.201933Z","submitted_at":"2026-06-12T16:51:29Z","title":"DeepLook: Deeper Thinking with Lookahead","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-02T11:32:12.529986Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.22602"},"observation_digest":"sha256:cc6f881c046e1ae0c588e68f274e1a86502c4d01a5d6ee45b4e8a266126ca8ec","observation_id":"5a251a68-a97a-4ce5-b030-4a30e0f7f6c3","resolution":{"observed_at":"2026-08-02T11:32:12.529986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-31T09:14:06.217834Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24647","last_updated":"2026-07-27T16:46:33Z","snapshot_observed_at":"2026-08-05T09:56:48.665074Z","submitted_at":"2026-07-27T16:46:33Z","title":"Efficiency Matters in Autonomous Research","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-31T09:14:06.217834Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.24647"},"observation_digest":"sha256:c436016719cb4b4eeb41cbaa2f17ce2cb9ae03922442e7b8dba48e6ef1f5e5fa","observation_id":"6a1af2cd-80d8-4ebf-ae96-b2c33cca27c7","resolution":{"observed_at":"2026-07-31T09:14:06.217834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-07-30T18:50:46.257802Z","title":"Language agent tree search unifies reasoning, acting, and planning in language models.arXiv preprint arXiv:2310.04406,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.26865","last_updated":"2026-07-29T12:47:05Z","snapshot_observed_at":"2026-08-02T19:28:19.003719Z","submitted_at":"2026-07-29T12:47:05Z","title":"Think Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM Agents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-30T18:50:46.257802Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.26865"},"observation_digest":"sha256:6fa90b5d1a32305a28f6cdcc16931724fd67a510b2f050c20b46e8881532cd1e","observation_id":"de4b7e55-dfb8-4707-8895-8bef7a3cd687","resolution":{"observed_at":"2026-07-30T18:50:46.257802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04406","snapshot_observed_at":"2026-08-03T14:33:31.992532Z","title":"arXiv preprint arXiv:2310.04406 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29055","last_updated":"2026-07-31T06:18:48Z","snapshot_observed_at":"2026-08-05T23:12:28.622067Z","submitted_at":"2026-07-31T06:18:48Z","title":"Autonomous Repair for Multi-Agent Systems via Monte-Carlo Tree Search","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-03T14:33:31.992532Z"},"links":{"cited_paper":"/paper/2310.04406","citing_paper":"/paper/2607.29055"},"observation_digest":"sha256:2c20e21940380ce66ae13ec20b5204c905e876919e94c7eb495d8c26ff803d98","observation_id":"c43f2d54-42b8-4fdb-8006-e9163d3bdddc","resolution":{"observed_at":"2026-08-03T14:33:31.992532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2310.04406/citation-record","integrity":"/paper/2310.04406/integrity","json":"/paper/2310.04406/citation-record.json","paper":"/paper/2310.04406"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.09687","last_updated":"2024-02-06T18:00:18Z","snapshot_observed_at":"2026-08-06T03:16:16.175894Z","submitted_at":"2023-08-18T17:29:23Z","title":"Graph of Thoughts: Solving Elaborate Problems with Large Language Models","version":4},"cited_work":{"arxiv_id":"2308.09687","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.09687","snapshot_observed_at":"2026-07-10T13:57:06.971993Z","title":"Besta, N","venue":"cs.CL","work_id":"34ed66c5-13ac-4799-b958-8e57d3de4705","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2308.09687","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:d4377d9f2ef8d9fa05f61988b1a74dd2b9f5224881a399774214b726829b4538","observation_id":"9b782529-0c06-47c0-8743-6190a714da5c","resolution":{"observed_at":"2026-05-16T23:26:04.473909Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":"2107.03374","doi":"10.48550/arxiv.2107.03374","metadata_source":"pith","pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Evaluating Large Language Models Trained on Code","venue":"cs.LG","work_id":"042493e9-b26f-4b4e-bbde-382072ca9b08","year":2021},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:d7f85b6ba20037c6851422ce9a7be5fecf256b6147d902b55c0884dce3bea2a5","observation_id":"1670ac2a-2c7c-447a-b2de-eefb37389b0c","resolution":{"observed_at":"2026-05-16T23:26:04.484065Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-01T08:08:23.404839+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T08:08:23.404839+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-04T15:46:25.710484Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":"2110.14168","doi":"10.1002/j.1545-","metadata_source":"pith","pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Training Verifiers to Solve Math Word Problems","venue":"cs.LG","work_id":"acab1aa8-b4d6-40e0-a3ee-25341701dca2","year":2021},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:3202028e2aa6d5847bb9ece96b93e3cf6f60ccdfedb232fed554a27b0ff0d406","observation_id":"461b9e93-8e8d-4a6d-9038-c0210aefadb4","resolution":{"observed_at":"2026-05-16T23:26:04.491682Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.04104","last_updated":"2024-04-17T17:41:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-01-10T18:12:16Z","title":"Mastering Diverse Domains through World Models","version":2},"cited_work":{"arxiv_id":"2301.04104","doi":"10.1126/sciadv.adu2488","metadata_source":"pith","pith_arxiv_id":"2301.04104","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mastering Diverse Domains through World Models","venue":"cs.AI","work_id":"6aeb260f-8c7c-4f9c-b98b-067cd7c59acd","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2301.04104","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:e93f2b45ab94e82f2f0cc790ad336637262ec863740248efb7e9fe2ef2463b97","observation_id":"8320b531-5f6f-4027-abdc-dd922fd5a58d","resolution":{"observed_at":"2026-05-16T23:26:04.498982Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17382","last_updated":"2024-06-24T05:25:21Z","snapshot_observed_at":"2026-08-03T23:03:20.128765Z","submitted_at":"2023-09-29T16:36:39Z","title":"Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency","version":3},"cited_work":{"arxiv_id":"2309.17382","doi":"10.48550/arxiv.2309.17382","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.17382","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reason for fu- ture, act for now: A principled framework for au- tonomous LLM agents with provable sample efficiency","venue":"arXiv (Cornell University)","work_id":"ba51c107-b4c4-45ab-a1ae-5164af8a0587","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2309.17382","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:0d6c82f09d8889f6eda9bac4f984e6b6a8afae71d829649b9ed698d84dbb7eaa","observation_id":"5e09e56c-51ed-4aa2-91a4-69606f0025ce","resolution":{"observed_at":"2026-05-16T23:26:04.506223Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:fa6ea28116e7fd7674c1c63befe32ccf127d8c9315c8d901e3d36fda3ec333a3","observation_id":"ac76a27e-59a5-4db6-a090-cd8447ebfab6","resolution":{"observed_at":"2026-05-16T23:26:04.513422Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.01815","last_updated":"2017-12-05T18:45:38Z","snapshot_observed_at":"2026-08-02T00:39:04.960144Z","submitted_at":"2017-12-05T18:45:38Z","title":"Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm","version":1},"cited_work":{"arxiv_id":"1712.01815","doi":"10.48550/arxiv.1712.01815","metadata_source":"pith","pith_arxiv_id":"1712.01815","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm","venue":"cs.AI","work_id":"9978bd70-b9dd-4eb6-928b-66c2d40da222","year":2017},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/1712.01815","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:029f32a3da3b17c50852e77a3177c9a752a9a4d5600f14b8e3f847b7d5d7cbe9","observation_id":"82bf8c01-107d-4a33-bae1-912a5bf63842","resolution":{"observed_at":"2026-05-16T23:26:04.520860Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-02T13:38:12.382503+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-02T13:38:12.382503+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-02T11:57:18.735747Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":"2307.09288","doi":"10.24963/ijcai.2025/706","metadata_source":"pith","pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","venue":"cs.CL","work_id":"68a5177f-d644-44c1-bd4f-4e5278c22f5d","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:cf62e6c06d827375b43fa32d68c6c8ac7f95a749bb373479e7a52a1e68859643","observation_id":"ebcae01d-38d2-4ee0-b554-ff2325e42cae","resolution":{"observed_at":"2026-05-16T23:26:04.527937Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16291","last_updated":"2023-10-19T16:27:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-25T17:46:38Z","title":"Voyager: An Open-Ended Embodied Agent with Large Language Models","version":2},"cited_work":{"arxiv_id":"2305.16291","doi":"10.18653/v1/2023.emnlp-main.118","metadata_source":"pith","pith_arxiv_id":"2305.16291","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Voyager: An Open-Ended Embodied Agent with Large Language Models","venue":"cs.AI","work_id":"ffe0d207-86cf-4742-a100-e988ac8b9676","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2305.16291","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:4d96ee775c848fadce4a4a28a33e472a487b2370639ae2913f0841c4c1cfe026","observation_id":"60f5b868-baf4-4da9-b03d-d1fb9d3dcb7c","resolution":{"observed_at":"2026-05-16T23:26:04.534478Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.00633","last_updated":"2023-10-26T01:43:17Z","snapshot_observed_at":"2026-07-06T15:21:46.324091Z","submitted_at":"2023-05-01T02:37:59Z","title":"Self-Evaluation Guided Beam Search for Reasoning","version":3},"cited_work":{"arxiv_id":"2305.00633","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.00633","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Decomposition enhances reasoning via self-evaluation guided decoding","venue":null,"work_id":"84f64f2f-3348-4bfe-8c2d-13fa2bcdf7b5","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"cited_paper":"/paper/2305.00633","citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:ed238f264e6a96caf386e4a314552d601d662c6dab339add5ad557a72a0a89b8","observation_id":"f37c3e8e-4d7f-4058-8e56-70d689951701","resolution":{"observed_at":"2026-05-16T23:26:04.542048Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"First in Sec","venue":null,"work_id":"057f4227-e70f-44eb-b75c-4c0ae848f5b5","year":2023},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:b6df7d9a395a55f7947f25b35d2b64e3cd7d6043acadfe1db2cfb92669501274","observation_id":"f5d99d75-1a80-4b6f-a834-aeaf560433df","resolution":{"observed_at":"2026-05-16T23:26:04.547110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"d4fbb8a5-e18b-460c-9d3f-e879986162c0","year":2011},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:28874705822349732e26be835dfaa15cdb4fb41e14dbf50ab5206ddc6fa16fc7","observation_id":"b9335e4c-16a3-4139-98a5-2e6b53fa64d0","resolution":{"observed_at":"2026-05-16T23:26:04.555011Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"Thus the correctness score is s","venue":null,"work_id":"1622e594-af0f-479a-b8d5-2cd66c03c2d9","year":1989},"citing_paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T23:26:04.445225Z"},"links":{"citing_paper":"/paper/2310.04406"},"observation_digest":"sha256:6a506b4c8360007f4cf36a60863cb181d5c38eb024c35e9accce739174483ec9","observation_id":"e967ecd9-7a41-4d78-86a5-82e0856551cd","resolution":{"observed_at":"2026-05-16T23:26:04.563131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2310.04406","last_updated":"2024-06-06T02:51:17Z","latest_version":3,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:55:11Z","title":"Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":1,"verified_exact":6,"verified_fuzzy":2},"total_outbound_references":13},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 81 inbound Pith citation observations for arXiv:2310.04406."}