{"as_of":"2026-08-18T04:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a4c100bd3b3aee1adb3ba768505fadc351ea1708edc1156fd7b44231e96fea87","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":15,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:21:39.923185Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-22T21:52:10.339402Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2401.03568","last_updated":"2024-01-25T21:20:27Z","snapshot_observed_at":"2026-08-12T12:11:22.336410Z","submitted_at":"2024-01-07T19:11:18Z","title":"Agent AI: Surveying the Horizons of Multimodal Interaction","version":2},"reference_index":132,"source":"arxiv_source","source_observed_at":"2026-05-18T14:25:58.876978Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2401.03568"},"observation_digest":"sha256:faeafe6b90c28d9fc2e330f012898b1e906c2367746408e484316b64527c8d96","observation_id":"a267bb68-80e1-4784-a762-e7098736d1bb","resolution":{"observed_at":"2026-05-18T14:25:59.398004Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2402.13116","last_updated":"2024-10-21T16:22:33Z","snapshot_observed_at":"2026-08-10T17:26:33.432994Z","submitted_at":"2024-02-20T16:17:37Z","title":"A Survey on Knowledge Distillation of Large Language Models","version":4},"reference_index":253,"source":"arxiv_source","source_observed_at":"2026-05-17T23:31:11.213552Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2402.13116"},"observation_digest":"sha256:c12860b06a5417c2ff96657cfb5656c5e22f2b58a616cfc9fbe74c7f21c83b52","observation_id":"dde232b1-c45a-4442-b872-c2a469705ee0","resolution":{"observed_at":"2026-05-17T23:31:11.764817Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-12T12:33:07.036176Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.17135","last_updated":"2024-11-26T06:04:10Z","snapshot_observed_at":"2026-08-14T15:52:44.410039Z","submitted_at":"2024-11-26T06:04:10Z","title":"LLM-Based Offline Learning for Embodied Agents via Consistency-Guided Reward Ensemble","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-12T12:33:07.036176Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2411.17135"},"observation_digest":"sha256:2d9d846aa2d43318ef90722135ab3a12a58b291154a9d4372c82bc16916eca6d","observation_id":"0e8b573a-27b6-44e9-98f1-209048e25e7b","resolution":{"observed_at":"2026-08-12T12:33:07.036176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-10T17:23:26.503804Z","title":"Ad- vances in neural information processing systems , 36","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12432","last_updated":"2025-05-25T13:59:04Z","snapshot_observed_at":"2026-08-17T13:39:18.693012Z","submitted_at":"2025-01-21T16:49:08Z","title":"Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-10T17:23:26.503804Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2501.12432"},"observation_digest":"sha256:3b1de34aca31fc6a35f94fcb1e9e7d3101ff4080f4cc747abe366f20c77c08c5","observation_id":"a8dfc220-aadb-4b64-a42c-9de334f1224d","resolution":{"observed_at":"2026-08-10T17:23:26.503804Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2503.16419","last_updated":"2025-08-21T19:14:40Z","snapshot_observed_at":"2026-08-11T13:10:23.709172Z","submitted_at":"2025-03-20T17:59:38Z","title":"Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models","version":4},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-14T01:29:56.480020Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2503.16419"},"observation_digest":"sha256:00c3e550b4fa025b917fe4c21dbc8fb888375f5a62fda17d4a67b0408cb5594b","observation_id":"a5f2e171-db24-412e-909f-9bedaa8a553c","resolution":{"observed_at":"2026-05-14T01:29:56.650210Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2503.21460","last_updated":"2025-03-27T12:50:17Z","snapshot_observed_at":"2026-07-06T20:59:35.694800Z","submitted_at":"2025-03-27T12:50:17Z","title":"Large Language Model Agent: A Survey on Methodology, Applications and Challenges","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-22T21:51:34.309870Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2503.21460"},"observation_digest":"sha256:aa834e4088cdf1b9df1d926609539e8b3d93b97be90ffd1e3b30c24339b4e515","observation_id":"3b1a1420-62da-4e8f-9434-2129f308fffb","resolution":{"observed_at":"2026-05-22T21:52:10.342172Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-16T12:21:39.923185Z","title":"Tree-planner: Efficient close-loop task planning with large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.13059","last_updated":"2025-04-17T16:14:24Z","snapshot_observed_at":"2026-08-16T12:13:26.460997Z","submitted_at":"2025-04-17T16:14:24Z","title":"RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T12:21:39.923185Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2504.13059"},"observation_digest":"sha256:18fc0430747225c949000fc91c517e63031b485229a605e73a2e0a561c760b97","observation_id":"3068e75f-089d-4703-8d4b-29db57085326","resolution":{"observed_at":"2026-08-16T12:21:39.923185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-07T15:01:47.987757Z","title":"Tree-planner: Efficient close-loop task planning with large language models.arXiv preprint arXiv:2310.08582, 2023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.987757Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:df5a3280c515c87feace13df05329e11240df1a35ffe479efb82f4b6c0a2c32a","observation_id":"402cca18-7e9a-4141-919a-75d7735f7b4d","resolution":{"observed_at":"2026-08-07T15:01:47.987757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-04T18:09:37.265636Z","title":"On the Move to Meaningful Internet Systems","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.10147","last_updated":"2025-09-12T11:20:11Z","snapshot_observed_at":"2026-08-16T07:27:01.460052Z","submitted_at":"2025-09-12T11:20:11Z","title":"Virtual Agent Economies","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T18:09:37.265636Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2509.10147"},"observation_digest":"sha256:867015e7e2e396b14167548c7ae1db685b620f5ad5e5c3aa95f79711bc397a3a","observation_id":"603945a5-64f1-43b2-bc48-6130f16d3b25","resolution":{"observed_at":"2026-08-04T18:09:37.265636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2509.21543","last_updated":"2026-06-22T21:20:43Z","snapshot_observed_at":"2026-08-15T15:44:21.263106Z","submitted_at":"2025-09-25T20:29:40Z","title":"Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-18T13:30:14.462351Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2509.21543"},"observation_digest":"sha256:a8053129ced6c755e8df24ff7a0486dc724f23cbe0ba4ed19d06b68d0a16311e","observation_id":"41f5cd3a-e77a-4378-a65e-2a041447b489","resolution":{"observed_at":"2026-05-18T13:31:24.742632Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-15T15:52:17.071946Z","title":"arXiv preprint arXiv:2310.08582 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.21543","last_updated":"2026-06-22T21:20:43Z","snapshot_observed_at":"2026-08-15T15:44:21.263106Z","submitted_at":"2025-09-25T20:29:40Z","title":"Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation","version":4},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-15T15:52:17.071946Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2509.21543"},"observation_digest":"sha256:47dcd96117ebb81cf10f7b7b8cda7af13ec4bbb4744f8430f222fe4488267251","observation_id":"bb06ad8e-de8e-4ea7-ba86-3d4cc160067f","resolution":{"observed_at":"2026-08-15T15:52:17.071946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2604.23194","last_updated":"2026-04-25T07:54:23Z","snapshot_observed_at":"2026-08-11T08:00:24.398283Z","submitted_at":"2026-04-25T07:54:23Z","title":"From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-08T08:10:36.579810Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2604.23194"},"observation_digest":"sha256:13bfd6d797083036bbf82ef0d1b8f10c0c9c873d41c40a98347b0de5c56dd083","observation_id":"5e63a20f-3dd4-4dad-a7cb-78aed7d8d142","resolution":{"observed_at":"2026-05-11T20:46:10.680981Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.08582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tree-planner: Efficient close- loop task planning with large language models","venue":null,"work_id":"43a644fc-4bc3-4e6b-970c-cae9aa4f3f0d","year":2023},"citing_paper":{"arxiv_id":"2605.06165","last_updated":"2026-05-07T12:51:49Z","snapshot_observed_at":"2026-08-17T00:27:13.360022Z","submitted_at":"2026-05-07T12:51:49Z","title":"Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost","version":1},"reference_index":177,"source":"arxiv_source","source_observed_at":"2026-05-08T10:19:08.451445Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2605.06165"},"observation_digest":"sha256:81d7e229a2b786af904dad3e69fb1099bf0e4043a51aa8cbaf2f0547f05cc15b","observation_id":"e0bdbc0e-00c5-43f5-9420-b04631e6f324","resolution":{"observed_at":"2026-05-11T20:06:09.651278Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-01T16:19:09.088543Z","title":"Tree-Planner: Efficient close-loop task planning with Large Language Models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-17T11:20:26.046175Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.088543Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a0b5284506af443747656753f02a8e48b76ca10a7bd97ae82826a26991127e80","observation_id":"c4ad41f1-67ba-4dcc-8e11-b7eac6c3f06c","resolution":{"observed_at":"2026-08-01T16:19:09.088543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-04T19:45:33.482658Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.01851","last_updated":"2026-08-03T07:58:35Z","snapshot_observed_at":"2026-08-17T12:44:12.584111Z","submitted_at":"2026-08-03T07:58:35Z","title":"Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-04T19:45:33.482658Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2608.01851"},"observation_digest":"sha256:adffdde86afeb6ce190394588357e5ec76b591136e7221b2dd63460d1f5bd7a7","observation_id":"5ff5a442-5eac-4b57-a50d-dc0a02d2e3ac","resolution":{"observed_at":"2026-08-04T19:45:33.482658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2310.08582/citation-record","integrity":"/paper/2310.08582/integrity","json":"/paper/2310.08582/citation-record.json","paper":"/paper/2310.08582"},"outbound":[],"paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T14:52:34.934742Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2310.08582."}