{"as_of":"2026-08-02T02:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1c6c7fafed11196a31aed063dc845f39884ebf3a028e80ee115c7b4b72514727","coverage":[{"denominator":112,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T16:19:09.540151Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-01T06:32:01.292127+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.18060/citation-record","integrity":"/paper/2607.18060/integrity","json":"/paper/2607.18060/citation-record.json","paper":"/paper/2607.18060"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-07-06T22:37:03.716474Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-08-01T16:19:08.878687Z","title":", title =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.878687Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:b6aae02ebb711579e7344fa925d6d4c38452a4cd7e3cdd2c6a79c1ff412480bc","observation_id":"50c05fc3-baf6-4854-a2ea-14ae29fb3a2b","resolution":{"observed_at":"2026-08-01T16:19:08.878687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.884664Z","title":"PDDLStream : Integrating symbolic planners and blackbox samplers via optimistic adaptive planning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.884664Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:f88270e3ef7391a372b1880b8d1d4be4c4eba0e1c8a32514c22c449fb614610b","observation_id":"58a5ba73-cbdd-4d4b-8f54-3c2b054e3550","resolution":{"observed_at":"2026-08-01T16:19:08.884664Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.890026Z","title":"From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models , journal=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.890026Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9c5829f19f664eb4e75ae752e4c66b5e8279da946aba7158fec44b6bb5d1f025","observation_id":"f662a881-d664-4f67-810b-d859cafff288","resolution":{"observed_at":"2026-08-01T16:19:08.890026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.895307Z","title":"Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.895307Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:814658365845e1747fbe4b24919c4accc6ff2166b14bc42d4e0b419175aaad1f","observation_id":"9ddb0a97-dc86-4a5a-87c4-6b7c7cc91587","resolution":{"observed_at":"2026-08-01T16:19:08.895307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.900431Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.900431Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:70d946a2aa1de0960f1c1bc80e7861017f4c173ab950b5ca9ee4d854d02f211f","observation_id":"08bd99e6-43b5-409f-9c3d-20b276d6d977","resolution":{"observed_at":"2026-08-01T16:19:08.900431Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.905289Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.905289Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:c7f91f2db0e29d82df176f2432c59c10ccbcd5068bbd83dc62a68ab04048a424","observation_id":"ee03b8a2-e8b7-4635-a8f0-7ed6c4f70668","resolution":{"observed_at":"2026-08-01T16:19:08.905289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:08.911711Z","title":"PR ompt Optimization in Multi-Step Tasks ( PROMST ): Integrating Human Feedback and Heuristic-based Sampling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:08.911711Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:d7a4606692490f1fc4a023dfbfae5b367ab33cdf9183d2469471fc67ad3a4727","observation_id":"9f3783fa-a504-4562-81f4-69a02777fb4e","resolution":{"observed_at":"2026-08-01T16:19:08.911711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.042591Z","title":"Proceedings of the 34th International Conference on Machine Learning , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.042591Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:ec2949adb201a3d80e793295b8041d6cd0ad4d4ca9d42361f921f4581c9147a3","observation_id":"b7bef96f-70fd-45a5-bf66-51f318a13c8b","resolution":{"observed_at":"2026-08-01T16:19:09.042591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.047938Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.047938Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:691125533663ae2d338211ec87ce3a8838fde9e2cb34a1288d1f50f9ba491a99","observation_id":"c450f7f2-0013-43a6-9f59-19974e7338fd","resolution":{"observed_at":"2026-08-01T16:19:09.047938Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.052873Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.052873Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:356bbe70effe3c1fb6b37878c9b53dbf87e4287bd78c699fab2d9f1ae3fa315f","observation_id":"da0d0288-592b-47cd-810b-ad5b39ab8ee3","resolution":{"observed_at":"2026-08-01T16:19:09.052873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.058046Z","title":"PaLM - E : An embodied multimodal language model","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.058046Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:7fd6ea2439e295d234fabc5f7492f6c7372dcfaff8ef92ce316eeab645c155b8","observation_id":"331b90dd-02bf-4a3c-9079-1bf45daae6d1","resolution":{"observed_at":"2026-08-01T16:19:09.058046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.063031Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.063031Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:24cbaff60848cb5ac29816542e01ae635b0767a35049cc67247269c677397282","observation_id":"ad1729b6-5ab0-4d98-a926-55736f07261c","resolution":{"observed_at":"2026-08-01T16:19:09.063031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.068394Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.068394Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:683bdef3be6fc528d271461d1ac0bca6a34cc333cb1144f1d04d970dc2c054fb","observation_id":"9d29c639-e366-4146-9af6-e66ab469e635","resolution":{"observed_at":"2026-08-01T16:19:09.068394Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.073090Z","title":"Guiding Long-Horizon Task and Motion Planning with Vision Language Models , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.073090Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:087abbf47b19b19a62ae5bb03415756279765d3d5c6f1b45d4c52aaf11fb71ce","observation_id":"ba6ac62c-c7dc-4e12-ae45-4d2d4eb5f053","resolution":{"observed_at":"2026-08-01T16:19:09.073090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.078309Z","title":"LLM -A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.078309Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:0263b9d32bf16911dd192216f10050030f6f052b9ed27dccc363157c2aefc904","observation_id":"851ffedc-ef6f-460d-9c05-bfe57e2cd398","resolution":{"observed_at":"2026-08-01T16:19:09.078309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.083557Z","title":"Generalized planning in pddl domains with pretrained 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":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.083557Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9a5fae8d3d4a09935fb920197271cf693f5cbadd8756fec967ee6febaa677168","observation_id":"9db15f77-75ed-49af-8772-a6188c318c80","resolution":{"observed_at":"2026-08-01T16:19:09.083557Z","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":"2026-07-06T16:32:07.186600Z","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":"2026-08-01T16:19:07.538499Z","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":"sha256:54cf6034ec0df6244b628279635dd55391699afded23d9dc6ecc4b85cdc7191b","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.093723Z","title":"Thirty-seventh Conference on Neural Information Processing Systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.093723Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:c8643fd4a02acb6be736aa7a23a511cc27854ac293039df6acf125d88cef8880","observation_id":"1c3986bb-41d7-4c05-836e-ad1f329620b9","resolution":{"observed_at":"2026-08-01T16:19:09.093723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23156","last_updated":"2025-02-28T19:50:42Z","snapshot_observed_at":"2026-07-06T19:42:21.306600Z","submitted_at":"2024-10-30T16:11:05Z","title":"VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23156","snapshot_observed_at":"2026-08-01T16:19:09.099592Z","title":"VisualPredicator : Learning abstract world models with Neuro-Symbolic Predicates for robot planning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.099592Z"},"links":{"cited_paper":"/paper/2410.23156","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:40203aa773118b8a0edab226557b6cdaae54905039e204830c2732f632f74f77","observation_id":"ccbbe1f9-e700-49b3-84df-6bdf58ab886f","resolution":{"observed_at":"2026-08-01T16:19:09.099592Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.106401Z","title":"Automated Planning Domain Inference for Task and Motion Planning , booktitle=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.106401Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:ce38f8ae81c28a248f1f046ad12692f6bfcbc5ab6b86fe1bba70d1f6c1824411","observation_id":"2f8bca33-5877-49cd-b493-36ef59081fb2","resolution":{"observed_at":"2026-08-01T16:19:09.106401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.112158Z","title":"One demo is all it takes: Planning Domain Derivation with LLMs from A single demonstration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.112158Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:51830892b7436b9dba46b069e1373e4bdc417f81453ceb07117fdd334c5f5216","observation_id":"eb5d9207-258c-4d10-a281-22d8e7ef80e5","resolution":{"observed_at":"2026-08-01T16:19:09.112158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.120435Z","title":"2024 , booktitle =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.120435Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:35e93b7a1b60484642edd268179784632fd33112a5f1c789a90195592bb56271","observation_id":"7399a969-a9e1-458c-9cfe-2df690f111e5","resolution":{"observed_at":"2026-08-01T16:19:09.120435Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.125933Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.125933Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9938f5b8698dab3115604260ca2f2e3968b625aeffa88e903bd56942c99ea512","observation_id":"342ba355-c694-4cd7-aa68-3ac35ae4a6e2","resolution":{"observed_at":"2026-08-01T16:19:09.125933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.131648Z","title":"Predicate Invention for Bilevel Planning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.131648Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:57f27ebffda621131e26e1f62166618f253ae22b60f18d9183958e9f0e4af7ca","observation_id":"8028c919-bd06-4ea7-890e-6190f7a42de3","resolution":{"observed_at":"2026-08-01T16:19:09.131648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.11477","last_updated":"2023-09-27T07:29:44Z","snapshot_observed_at":"2026-08-01T15:58:01.346044Z","submitted_at":"2023-04-22T20:34:03Z","title":"LLM+P: Empowering Large Language Models with Optimal Planning Proficiency","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.11477","snapshot_observed_at":"2026-08-01T16:19:09.138301Z","title":"LLM+P : Empowering large language models with optimal planning proficiency","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.138301Z"},"links":{"cited_paper":"/paper/2304.11477","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:138e8b889469221730371e29064d6f420437bb0b81c28b63722c4a237803a015","observation_id":"42925ab8-3207-4e44-84a0-67932f5b41db","resolution":{"observed_at":"2026-08-01T16:19:09.138301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.144681Z","title":"2024 IEEE International conference on robotics and automation (ICRA) , year=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.144681Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:2c30a6cb7aad69ce10901ad701037e77427c9e19217072052d2479f3cefce22f","observation_id":"f7719203-b5ae-4277-bdc1-1cdb5a3b305f","resolution":{"observed_at":"2026-08-01T16:19:09.144681Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.151494Z","title":"Learning to Search in Task and Motion Planning With Streams","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.151494Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:b81ed5c37f9c844aa83679bed450e1f5d7dc7ee59d95f1dc71f837063e625c1d","observation_id":"8dbcc4a3-dfc6-42df-9e7a-625bec2a16e3","resolution":{"observed_at":"2026-08-01T16:19:09.151494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-01T16:19:09.157976Z","title":"arXiv preprint arXiv:2410.21276 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.157976Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:1a0eaf2a1c6793b46fa809cbc0650cf6c6926bc07f060fbfd61b9d9455671ed4","observation_id":"3a9f860a-ed8f-4561-93cc-faed0c1fc5e7","resolution":{"observed_at":"2026-08-01T16:19:09.157976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.163871Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.163871Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:c6c6babd5058be55d8a7a0ddcf62a69cec21aca314a1c6a5eb5ccc8414dd7e86","observation_id":"5a67648b-680c-4895-80ce-15ca3121df67","resolution":{"observed_at":"2026-08-01T16:19:09.163871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.169105Z","title":"8th Annual Conference on Robot Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.169105Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:5e198b650910f82673e4e61646cbafdaf1a53f080ac123f8265847c1c64e315b","observation_id":"d25f1995-52e9-40a3-ae6d-39bc27e86ba6","resolution":{"observed_at":"2026-08-01T16:19:09.169105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.174066Z","title":"2025 IEEE International Conference on Robotics and Automation (ICRA) , year=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.174066Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:04663a2d704abfd41dd9e5af4ebe6ce905176556c52257727232fcdee468607a","observation_id":"76d7cc7d-5525-4966-9697-10065ffc23dc","resolution":{"observed_at":"2026-08-01T16:19:09.174066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.179437Z","title":"Language Models can infer action semantics for symbolic planners from environment feedback","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.179437Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a4ce88595f4e92b3b6083d68b900ad89dd9b08eb72cbf56e405f36348d78f707","observation_id":"5f4c4e9f-4484-4758-84a2-190ae08a18a4","resolution":{"observed_at":"2026-08-01T16:19:09.179437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.184565Z","title":"Robotics: Science and Systems (RSS) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.184565Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:efe373965174db6385587abf43a2cff379b2a9795f8d223a94a7983f75e29a58","observation_id":"c557aa79-3ebc-493a-9432-4ac45b78b9e5","resolution":{"observed_at":"2026-08-01T16:19:09.184565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.189293Z","title":"Proceedings of The 7th Conference on Robot Learning , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.189293Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:bad25688f5b39df9390c75a2e1f2a5d8f18f243960d63e13b53d45eaeb39d2eb","observation_id":"366571f6-5165-4293-8224-b875d778c5b2","resolution":{"observed_at":"2026-08-01T16:19:09.189293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.194051Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.194051Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9134a06f767c597765af626de8d24acb35dcde314527d79ecf1fbd871e53fccc","observation_id":"52b6e325-2021-4b86-9976-209adcf764f6","resolution":{"observed_at":"2026-08-01T16:19:09.194051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.198996Z","title":"2023 , journal =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.198996Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:e1fae1c0b4bfd756a8b5d8e6580fc8e56a31a24ee73450fed7aa1e4a3cc478d3","observation_id":"56e4844a-dedb-41d5-8875-0436a2296903","resolution":{"observed_at":"2026-08-01T16:19:09.198996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.204850Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.204850Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:8065cf7b936afbfd0d3dd72f0147db39dbd4d73c19e8cfae81027f23f0ac9f4d","observation_id":"31fa4285-947b-4613-a0ba-bdc9b8098ffe","resolution":{"observed_at":"2026-08-01T16:19:09.204850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.209734Z","title":"Self-training meets consistency: Improving LLMs’ reasoning with consistency-driven rationale evaluation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.209734Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:6b1c0e37d14e20788fd49881620623f116ef424fa83ee1f7bbe969cac1d8ee84","observation_id":"6f3a398b-73d5-4f09-8dff-8f28b532815f","resolution":{"observed_at":"2026-08-01T16:19:09.209734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.214874Z","title":"V-STaR: Training verifiers for self-taught reasoners","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.214874Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a465d72d458e5e60ac0956d5c411b90b3df5af171fee8648bf6876f3cdb252fd","observation_id":"e070f32f-14e7-442c-b00e-40b1324bc62d","resolution":{"observed_at":"2026-08-01T16:19:09.214874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.220151Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.220151Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:33e3c6f64eb0798b97e352dcbe9577b054fbc226ece219522f64836025fa36cb","observation_id":"2fb42ef6-7560-41d7-99a0-565517381693","resolution":{"observed_at":"2026-08-01T16:19:09.220151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.224941Z","title":"and Le, Quoc V","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.224941Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9c2df47b9d8be8af6cb71379b984267b283057cb06590b210ce0b62ec307182b","observation_id":"236b00c9-1fee-480c-8208-9ac6461ebb46","resolution":{"observed_at":"2026-08-01T16:19:09.224941Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.229618Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.229618Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:552ec483316899c9f74afa26849c86578c05cc7232b538ee38f2e3777ee9bfbd","observation_id":"3d60e958-0207-4433-9d31-f50a34365a6e","resolution":{"observed_at":"2026-08-01T16:19:09.229618Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.234045Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.234045Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:f005741fe01a6299cd875d9f95b3775f6af52c62c783c606971c2d6563b9a703","observation_id":"e3dc2175-5fda-43b2-8536-f09aba7f95f2","resolution":{"observed_at":"2026-08-01T16:19:09.234045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.238622Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.238622Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:415f8c3c0158575c741f6fb8ac7bca8fee33d159792c2d94ed3d81afc2c9b477","observation_id":"d77fd5d9-f55b-47ae-99be-28db8a34a2f6","resolution":{"observed_at":"2026-08-01T16:19:09.238622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-01T16:19:09.243340Z","title":"arXiv preprint arXiv:2110.14168 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.243340Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:76ed5aceadf601778f1d59857866965c661b10bc3e14d12b4dc3ff3abb99b056","observation_id":"7fba14af-800d-4bc5-b538-08de23d1291f","resolution":{"observed_at":"2026-08-01T16:19:09.243340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.249292Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.249292Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:3b2155cd14cc3effa3ed518c9a3ab9dbf8bef6acf356cb17f6c42c63f3ac68c5","observation_id":"0cdffd52-c250-4751-933c-e7d577151d28","resolution":{"observed_at":"2026-08-01T16:19:09.249292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.253853Z","title":"8th Annual Conference on Robot Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.253853Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a300dbc0c5789759a340d28011dc469f8cbc5f74779c89cbeafe184bc9b5d6bd","observation_id":"1175553e-4d32-46d6-9d45-62500ba0d4de","resolution":{"observed_at":"2026-08-01T16:19:09.253853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.258804Z","title":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , year=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.258804Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:acf519380bf03494da74cb74f9d0952b22108e6f1362453e6c72d70441edb6af","observation_id":"f30c5824-cb0c-4a81-a5a3-995f6a5f8341","resolution":{"observed_at":"2026-08-01T16:19:09.258804Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.264871Z","title":"P roof W riter: Generating Implications, Proofs, and Abductive Statements over Natural Language","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.264871Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:6d3ebde96ce10ec54f6ae4da5fc6e4f05533efde5b47eb92d300d34c09e41c40","observation_id":"64af1046-3b38-43a5-9256-ea29b081fba1","resolution":{"observed_at":"2026-08-01T16:19:09.264871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.269954Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.269954Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:cbaeed4c5d4442f1b43cd28157ca6a19893114abe30ad56324dbe059155cf6f4","observation_id":"68cb53c6-2c3a-42ee-9368-4731d2c8815a","resolution":{"observed_at":"2026-08-01T16:19:09.269954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.276079Z","title":"Annual Meeting of the Association for Computational Linguistics , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.276079Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:e57862b460ef1cd860d52ac2a97ccb75f6f51dbec476d42c3f23e3eb4e543dec","observation_id":"193a4afe-7873-4da8-8e06-47275f672ed3","resolution":{"observed_at":"2026-08-01T16:19:09.276079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.281687Z","title":"Logic- LM : Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.281687Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:5836bc0ef044b12bc2aab00cbc7c963dc785430fe7aeaf6d58d5b83b54d38db7","observation_id":"dc6dffe1-a2c4-4f5a-80ea-bda9424cef8b","resolution":{"observed_at":"2026-08-01T16:19:09.281687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.286511Z","title":"FOLIO : Natural Language Reasoning with First-Order Logic","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.286511Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:3e8775c1b59be731c48c03f90e71fe9f20695679cad10bf9f146f4e48f6a3da1","observation_id":"ed4519b2-ca2b-4f5c-b02e-5e87731d6a03","resolution":{"observed_at":"2026-08-01T16:19:09.286511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.292056Z","title":"LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers , booktitle=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.292056Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:bbfb027ed6f1c40859f5682f6b0ac27db62b1cc9ae7aaee44f97d5b7bd0ed21d","observation_id":"8e5f5137-a548-441c-9947-9ed316c2253d","resolution":{"observed_at":"2026-08-01T16:19:09.292056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.297221Z","title":"Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA) , year =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.297221Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a8c6034fc2d3a6db15a67ee37a8b5032a8a1e788ac23a318e96578c3dbed7e1f","observation_id":"35184324-8d29-4914-9cf8-a712bf888661","resolution":{"observed_at":"2026-08-01T16:19:09.297221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.303527Z","title":"Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.303527Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:84ec66263066fac5d2752616aa362fb14f675e0abb3a236324b47dafeaa1bcf4","observation_id":"0721eb25-5633-49f5-a6f6-aa49c436507d","resolution":{"observed_at":"2026-08-01T16:19:09.303527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.308983Z","title":"The FF planning system: Fast plan generation through heuristic search","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.308983Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:b0917a648802f84b512648f5af7bd4f088e1c3e8b806fcfc10e1f35ae2ced018","observation_id":"b68784c7-1726-41e2-93ad-5df7eb4b629e","resolution":{"observed_at":"2026-08-01T16:19:09.308983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.315365Z","title":"and Khashabi, Daniel and Hajishirzi, Hannaneh","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.315365Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a29480aa478a855dbfc413cbb7b9d1c2603019fa501d5ba128c56e3ce027257a","observation_id":"122dbe3f-90df-4180-8f53-ced7e282e3f5","resolution":{"observed_at":"2026-08-01T16:19:09.315365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.320835Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.320835Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:5b60d142b2b9eb5bc079e8bcc6808df25fc3b7327a93283ecd84b50ed5bfcec7","observation_id":"2c4a6624-ae57-446b-9696-6244640b806c","resolution":{"observed_at":"2026-08-01T16:19:09.320835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.19786","last_updated":"2025-03-25T15:52:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-25T15:52:34Z","title":"Gemma 3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.19786","snapshot_observed_at":"2026-08-01T16:19:09.326564Z","title":"Gemma 3 Technical Report","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.326564Z"},"links":{"cited_paper":"/paper/2503.19786","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:519e4bd235289b0b02f6b6ec896de535a56de0294348522d56d56a8a089d4962","observation_id":"67965d00-bf82-4a5a-a9b7-545e7ca71af3","resolution":{"observed_at":"2026-08-01T16:19:09.326564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.08584","last_updated":"2026-01-13T14:06:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-01-13T14:06:03Z","title":"Ministral 3","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.08584","snapshot_observed_at":"2026-08-01T16:19:09.332083Z","title":"arXiv preprint arXiv:2601.08584 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.332083Z"},"links":{"cited_paper":"/paper/2601.08584","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:b37064bcffb3ecac45aef92695629003f7ab2cbe93b63739731047c5447969d7","observation_id":"0d10358e-a338-489f-924a-d451b954988e","resolution":{"observed_at":"2026-08-01T16:19:09.332083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-01T16:19:09.337678Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.337678Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:9173e49f404fdd8acb53c823017c8193504eac4a70397c794f8f122dc91b90b3","observation_id":"88d4b2cf-b351-4a8a-bab4-5b398c6355be","resolution":{"observed_at":"2026-08-01T16:19:09.337678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.343450Z","title":"_0 : A vision-language-action flow model for general robot control","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.343450Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:613123cd5c7e4f88f597dd3096a118c7c5249094fc7c6e23c671e3f52a1a7f7b","observation_id":"9768e662-a595-4120-a7d0-4b7db0a43a51","resolution":{"observed_at":"2026-08-01T16:19:09.343450Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.349119Z","title":"Leveraging Language-based Representations for Better Solving Symbol-related Problems with Large Language Models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.349119Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:bdaeb3928916bc80a7d94ca005ea6646286d33f1639d00d255d2933f7c2cb34a","observation_id":"16cc7e52-958e-4527-877e-a96ce3a233e8","resolution":{"observed_at":"2026-08-01T16:19:09.349119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.355079Z","title":"Language Models can be Deductive Solvers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.355079Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:16f1af4138111689b8023655592e0f5c0e34cd30ed6a6ccd7c692930a1eecd62","observation_id":"3adaad89-9cef-40c5-a83f-0917c14452ea","resolution":{"observed_at":"2026-08-01T16:19:09.355079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.362563Z","title":"Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.362563Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:5e7a1c91e3eb145f7137c7e01726d4287b2ac8a91304751025e53854ceef6fdf","observation_id":"386c7ae8-4e45-48f7-9706-3997fe250bb8","resolution":{"observed_at":"2026-08-01T16:19:09.362563Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.368721Z","title":"Proximal Policy Optimization Algorithms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.368721Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a2d06a20e827e35e3e278bb2777b8f497a3af6c3b85425ebf45553210a23e683","observation_id":"84d0d508-9c07-4ffd-8d21-8f5619ee4633","resolution":{"observed_at":"2026-08-01T16:19:09.368721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-01T16:19:09.374881Z","title":"arXiv preprint arXiv:2402.03300 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.374881Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:7dc30ca4f4519fcd3d80638f78fffcd84c194c42c5998c9792e8c63358146e82","observation_id":"f3192980-ea8c-478f-b52b-43b95e4eb77e","resolution":{"observed_at":"2026-08-01T16:19:09.374881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.380937Z","title":"Deep Reinforcement Learning from Human Preferences , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.380937Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:908b25d7a5331b4a5cd90dd48554239a96af4554fb8fcc95c0f62394f7123737","observation_id":"b3c0e181-8742-4306-af4e-b6363ebb17b4","resolution":{"observed_at":"2026-08-01T16:19:09.380937Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.386273Z","title":"Thirty-seventh Conference on Neural Information Processing Systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.386273Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:951e88b69e49c3e87e55aae0bc36b58c4ee9c90ee16e18747e6f6ca27260cdb0","observation_id":"6aba837c-f80d-4286-b2c7-69ea156cd918","resolution":{"observed_at":"2026-08-01T16:19:09.386273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.391007Z","title":"9th Annual Conference on Robot Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.391007Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:3e11d88abd1e9e496968b258511624fdb259ee1229d3a47d6dced5575462687c","observation_id":"3dbf8f4b-01a5-4e91-9379-21fc9772c2af","resolution":{"observed_at":"2026-08-01T16:19:09.391007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.396601Z","title":"Proceedings of the International Conference on Automated Planning and Scheduling , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.396601Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:8bdcc42a602f9a7962a20f60d6053950037862156fddb7168681f11ba84eaa29","observation_id":"03fa7656-eb9d-4691-a703-5608e7023ba7","resolution":{"observed_at":"2026-08-01T16:19:09.396601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16151","last_updated":"2023-05-25T15:21:09Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:21:09Z","title":"Understanding the Capabilities of Large Language Models for Automated Planning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16151","snapshot_observed_at":"2026-08-01T16:19:09.402294Z","title":"arXiv preprint arXiv:2305.16151 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.402294Z"},"links":{"cited_paper":"/paper/2305.16151","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:752b0dd751d6e6893bd533f12d254ae50efb99fadb4d46858522fc2f67d2e3bf","observation_id":"2239283a-12c9-4a36-a19e-0853b853a4db","resolution":{"observed_at":"2026-08-01T16:19:09.402294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.408284Z","title":"2026 , journal=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.408284Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:38131c4ad0636202dc6cbd3c4e00918c9324e13a338ee20f9f8c8182150b5477","observation_id":"e98cc004-d6b8-4949-a73d-f6977041f784","resolution":{"observed_at":"2026-08-01T16:19:09.408284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.413334Z","title":"UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.413334Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:8f0d2ce074225b5a572df6b1f6029c6775fe781ef3be1fb0508b9af7b94fae8d","observation_id":"8b047dd4-0c94-41b6-8501-416bc3d13124","resolution":{"observed_at":"2026-08-01T16:19:09.413334Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.02881","last_updated":"2026-05-08T04:21:51Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-04T17:51:21Z","title":"MolmoAct2: Action Reasoning Models for Real-world Deployment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.02881","snapshot_observed_at":"2026-08-01T16:19:09.418294Z","title":"arXiv preprint arXiv:2605.02881 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.418294Z"},"links":{"cited_paper":"/paper/2605.02881","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:7a951058f89aa2521d781cbc1d170ca9f94a9895c3c64f48a788601259b4211c","observation_id":"0fd56c30-abf1-46c4-9068-942911e35c7f","resolution":{"observed_at":"2026-08-01T16:19:09.418294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2510.10274","last_updated":"2025-10-11T16:20:17Z","snapshot_observed_at":"2026-07-06T22:32:22.953630Z","submitted_at":"2025-10-11T16:20:17Z","title":"X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2510.10274","snapshot_observed_at":"2026-08-01T16:19:09.424307Z","title":"arXiv preprint arXiv:2510.10274 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.424307Z"},"links":{"cited_paper":"/paper/2510.10274","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:234c561e520811cd20ecf6b587fd0b8cbe57ea67e947603d6ec1983d823b1a2a","observation_id":"0de7cf1d-cdd9-432d-9325-fd708f1f43f5","resolution":{"observed_at":"2026-08-01T16:19:09.424307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.429489Z","title":"arXiv preprint arXiv:2510.06710 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.429489Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:c8aa454a69560c3f4224ae6a3004d66bb4cdcbbffd81fdc0577080af435f008a","observation_id":"993161e1-81ee-4506-8e49-a96336842d7b","resolution":{"observed_at":"2026-08-01T16:19:09.429489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.434371Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.434371Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:0813443e85b6ca5e8268339b484fd3abd41ce087be8de033f6fefa6c3d86f646","observation_id":"8404be0f-8a2d-4a05-9835-6f3af5958e3f","resolution":{"observed_at":"2026-08-01T16:19:09.434371Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.439332Z","title":"2011 IEEE international conference on robotics and automation , year=","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.439332Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:24d5b13ee80425ebf40bc0c8ceb07caca320136c47d491582e718ca5b2336ad5","observation_id":"413eb35c-9b51-476b-a2c2-22ed60b46607","resolution":{"observed_at":"2026-08-01T16:19:09.439332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2603.22078","last_updated":"2026-07-30T02:24:57Z","snapshot_observed_at":"2026-08-02T02:16:10.817775Z","submitted_at":"2026-03-23T15:13:15Z","title":"Do World Action Models Generalize Better than VLAs? A Robustness Study","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.22078","snapshot_observed_at":"2026-08-01T16:19:09.444916Z","title":"arXiv preprint arXiv:2603.22078 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.444916Z"},"links":{"cited_paper":"/paper/2603.22078","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:2ef22eca96279bbb884f2c2c62ec188d109e67acd3b341af83ff3dfee28926af","observation_id":"cb89ec46-e1c9-4afd-aec8-70d0fbc37ac2","resolution":{"observed_at":"2026-08-01T16:19:09.444916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.450128Z","title":"Annual review of control, robotics, and autonomous systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.450128Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:b87edd0f16255498aac2bc441861224ed259858d267c21760f0aa9add4b11b24","observation_id":"7a540708-74bc-43b8-8cd1-3d182128b081","resolution":{"observed_at":"2026-08-01T16:19:09.450128Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03629","last_updated":"2023-03-10T01:00:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-06T01:00:32Z","title":"ReAct: Synergizing Reasoning and Acting in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03629","snapshot_observed_at":"2026-08-01T16:19:09.455113Z","title":"arXiv preprint arXiv:2210.03629 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.455113Z"},"links":{"cited_paper":"/paper/2210.03629","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:a28c6e244b29a9bbfc572390254732e7873a70115012fb9678482d505c4e4ca2","observation_id":"5f8e3dfe-e0dc-41ab-8e25-ee744a8a2250","resolution":{"observed_at":"2026-08-01T16:19:09.455113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.460290Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.460290Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:364c27f51862edb5d8d938a16d918f89f059b752d967a8f0841a72fcff09d65d","observation_id":"97345006-bf33-4082-8820-99b5bb833690","resolution":{"observed_at":"2026-08-01T16:19:09.460290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.465072Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.465072Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:1f1728f119a3d71acaa64ba2479087303709241a9423d5218dd8dd3f773a9c3f","observation_id":"2b97a56f-fcd6-4a6f-92e4-cfeaad0fe476","resolution":{"observed_at":"2026-08-01T16:19:09.465072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16291","snapshot_observed_at":"2026-08-01T16:19:09.470463Z","title":"arXiv preprint arXiv:2305.16291 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.470463Z"},"links":{"cited_paper":"/paper/2305.16291","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:589fd7bccbb9f930efa2d2972e898da2568cb4da8ab661c09677982f61ca8be8","observation_id":"3b20f65b-7b73-444c-9cfc-f226553ece24","resolution":{"observed_at":"2026-08-01T16:19:09.470463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.475525Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.475525Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:869879c9c537f1247a7a823cfa247234749fa7920a117ebbb7981cd3060e9970","observation_id":"0dedd20b-5b70-4e36-88af-cd972d8a90a9","resolution":{"observed_at":"2026-08-01T16:19:09.475525Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.480544Z","title":"Forty-first International Conference on Machine Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.480544Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:23cbc9f6b06ad065a53e8b14522b4aaceede9fff3ec3d03f48bf0d6448e4ba75","observation_id":"20932d70-a708-4e60-af4c-d2ce95c52491","resolution":{"observed_at":"2026-08-01T16:19:09.480544Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.485449Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.485449Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:05ca8d842d33af1fbcc35cfd590bdbbe6b5ee89eabf4ff5ad25d8423e47c034e","observation_id":"afd81873-b3d2-4616-a971-2b9be68ec250","resolution":{"observed_at":"2026-08-01T16:19:09.485449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01489","last_updated":"2024-10-29T17:29:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-01T17:24:45Z","title":"Agentless: Demystifying LLM-based Software Engineering Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01489","snapshot_observed_at":"2026-08-01T16:19:09.490101Z","title":"arXiv preprint arXiv:2407.01489 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.490101Z"},"links":{"cited_paper":"/paper/2407.01489","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:3e82f9979d033a4a62a661d3897e7dbfa44ab8dbe2ba8ffcfc23378c5930ec7f","observation_id":"155cc97a-b899-4669-ab69-3e3318f88127","resolution":{"observed_at":"2026-08-01T16:19:09.490101Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08155","last_updated":"2023-10-03T20:47:10Z","snapshot_observed_at":"2026-07-31T19:03:03.494918Z","submitted_at":"2023-08-16T05:57:52Z","title":"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08155","snapshot_observed_at":"2026-08-01T16:19:09.495017Z","title":"arXiv preprint arXiv:2308.08155 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.495017Z"},"links":{"cited_paper":"/paper/2308.08155","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:09007314792e2fb4036ea3b87c2313e3c738c1a51c29de8641d0905e2f7aad83","observation_id":"2c4d3fea-cb97-42e4-b06d-7563bd1b4cbd","resolution":{"observed_at":"2026-08-01T16:19:09.495017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.500613Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.500613Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:680657e4d06bc9f7baa884e892204442ae65c2771050ba20257ec92f37df912e","observation_id":"a38d2ba1-daad-45b9-a850-97c755c34895","resolution":{"observed_at":"2026-08-01T16:19:09.500613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.505369Z","title":"arXiv preprint arXiv:2603.11558 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.505369Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:bc1f620408dd1ad140708de58c1af5ab4b00cc7debd7a36de34fac382bc658fb","observation_id":"241e74a7-28ce-465e-8792-b0562a9622d2","resolution":{"observed_at":"2026-08-01T16:19:09.505369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.19980","last_updated":"2026-06-18T09:21:27Z","snapshot_observed_at":"2026-07-06T23:55:10.536884Z","submitted_at":"2026-06-18T09:21:27Z","title":"ENPIRE: Agentic Robot Policy Self-Improvement in the Real World","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.19980","snapshot_observed_at":"2026-08-01T16:19:09.510548Z","title":"arXiv preprint arXiv:2606.19980 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.510548Z"},"links":{"cited_paper":"/paper/2606.19980","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:99d8d32b87089aefd0df1f276837b09378a7e9b00ffdc7c340ed395adeef80a8","observation_id":"88c8f65c-5bb6-4bad-a27d-9229206d5fb7","resolution":{"observed_at":"2026-08-01T16:19:09.510548Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.515542Z","title":"arXiv preprint arXiv:2602.11291 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.515542Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:dd9b4724e09e87cb06088fd8a72dcb49b77da94e0ca8cbafb83d849ec49f3f9e","observation_id":"c70183f4-4b1d-4dd2-a9d0-d500882a440d","resolution":{"observed_at":"2026-08-01T16:19:09.515542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.520953Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.520953Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:def7508afeb0190b12e19e0fefc2b4ea042311e7c71638f6b9f005a067c9fdb1","observation_id":"8283fad7-38fe-4014-9bcd-750564a421fb","resolution":{"observed_at":"2026-08-01T16:19:09.520953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.07999","last_updated":"2021-11-15T18:59:03Z","snapshot_observed_at":"2026-07-06T12:08:46.570529Z","submitted_at":"2021-11-15T18:59:03Z","title":"Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.07999","snapshot_observed_at":"2026-08-01T16:19:09.525689Z","title":"arXiv preprint arXiv:2111.07999 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.525689Z"},"links":{"cited_paper":"/paper/2111.07999","citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:d3dfb484de6bd7e2af87742637f51d5cb108d4685071ec06599115f70f5fe6b4","observation_id":"723389e3-86bc-4ff5-96c2-99e4bda0cfda","resolution":{"observed_at":"2026-08-01T16:19:09.525689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.530560Z","title":"International conference on learning representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.530560Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:bcf236975b477845cf1bc84355e192581ac209d05bf9ccf1b24df9234e0f2b8d","observation_id":"7fc1c70f-2394-4b92-af87-caac4c0b5ba7","resolution":{"observed_at":"2026-08-01T16:19:09.530560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.535624Z","title":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.535624Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:389f3ca128184b90d2f5858e5f4de3a20add97aac7477865b21564e36b9cc1c5","observation_id":"6c914c8c-be2f-49f3-8af5-68f7ec6ab359","resolution":{"observed_at":"2026-08-01T16:19:09.535624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:19:09.540151Z","title":"Conference on Robot Learning , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning","version":2},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-01T16:19:09.540151Z"},"links":{"citing_paper":"/paper/2607.18060"},"observation_digest":"sha256:403e83142ce03bfb65e4541a0333517151d9ade1ae05b94c3eb3099678aed927","observation_id":"382273bf-450d-4a41-86cf-90737f854a14","resolution":{"observed_at":"2026-08-01T16:19:09.540151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.18060","last_updated":"2026-07-28T09:02:58Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-01T16:19:07.538499Z","submitted_at":"2026-07-20T15:27:13Z","title":"RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":100,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":112},"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":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"thesis":"As of 2 August 2026, this Paper Citation Record lists 100 of 112 outbound references and 0 inbound Pith citation observations for arXiv:2607.18060."}