{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CWXQ7IIQM65L3DDGSCWPGYWWO2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e1260009a2b8e569fe404ef4bfe3c8b06ac431309698616e7e8871c17c9e2f7f","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2023-09-27T18:40:36Z","title_canon_sha256":"6b62b34a0d732ca68cff3543cf06133e9b6155cc74251fbe6564e006b0ba8f19"},"schema_version":"1.0","source":{"id":"2309.15943","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.15943","created_at":"2026-07-05T07:59:18Z"},{"alias_kind":"arxiv_version","alias_value":"2309.15943v2","created_at":"2026-07-05T07:59:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.15943","created_at":"2026-07-05T07:59:18Z"},{"alias_kind":"pith_short_12","alias_value":"CWXQ7IIQM65L","created_at":"2026-07-05T07:59:18Z"},{"alias_kind":"pith_short_16","alias_value":"CWXQ7IIQM65L3DDG","created_at":"2026-07-05T07:59:18Z"},{"alias_kind":"pith_short_8","alias_value":"CWXQ7IIQ","created_at":"2026-07-05T07:59:18Z"}],"graph_snapshots":[{"event_id":"sha256:de28360c830a742a024255208feb6fa3831d35e34ce4577a18107349d54d7c73","target":"graph","created_at":"2026-07-05T07:59:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2309.15943/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A flurry of recent work has demonstrated that pre-trained large language models (LLMs) can be effective task planners for a variety of single-robot tasks. The planning performance of LLMs is significantly improved via prompting techniques, such as in-context learning or re-prompting with state feedback, placing new importance on the token budget for the context window. An under-explored but natural next direction is to investigate LLMs as multi-robot task planners. However, long-horizon, heterogeneous multi-robot planning introduces new challenges of coordination while also pushing up against ","authors_text":"Chuchu Fan, Jacob Arkin, Nicholas Roy, Yang Zhang, Yongchao Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2023-09-27T18:40:36Z","title":"Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.15943","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:dc675bc5a19de527b56f9177ef1198e4adadc90dde8edf9b85e409d577260efb","target":"record","created_at":"2026-07-05T07:59:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e1260009a2b8e569fe404ef4bfe3c8b06ac431309698616e7e8871c17c9e2f7f","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.RO","submitted_at":"2023-09-27T18:40:36Z","title_canon_sha256":"6b62b34a0d732ca68cff3543cf06133e9b6155cc74251fbe6564e006b0ba8f19"},"schema_version":"1.0","source":{"id":"2309.15943","kind":"arxiv","version":2}},"canonical_sha256":"15af0fa11067babd8c6690acf362d67680d2fa2770f0ba3ff1cec1e802c40b77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"15af0fa11067babd8c6690acf362d67680d2fa2770f0ba3ff1cec1e802c40b77","first_computed_at":"2026-07-05T07:59:18.300873Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:59:18.300873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nmRwR+OwEhIJe4q8NmDtE+FImEYkoXUG/UyswTYE/anLm+pskezYNEqd+9T9MBuraQGw3b1MXzW1lRH9OkBeBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:59:18.301370Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.15943","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dc675bc5a19de527b56f9177ef1198e4adadc90dde8edf9b85e409d577260efb","sha256:de28360c830a742a024255208feb6fa3831d35e34ce4577a18107349d54d7c73"],"state_sha256":"820bd43dc01869a957bd2e251d3f0f5cf43cc7b43ee5a55aeeb0eed6218a99ed"}