{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GIVMQGOLK3IRUZ6CDU5JO7DAF2","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":"6ba050380609cb2be00fafd8e343c168ac7f9967086510773036601961ad96ea","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-30T09:42:54Z","title_canon_sha256":"5092a4b44a7bd6e73f278a82975105c8cfe50e65ec6624561df57e4c3ff9623a"},"schema_version":"1.0","source":{"id":"2405.19883","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19883","created_at":"2026-07-05T08:46:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19883v2","created_at":"2026-07-05T08:46:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19883","created_at":"2026-07-05T08:46:25Z"},{"alias_kind":"pith_short_12","alias_value":"GIVMQGOLK3IR","created_at":"2026-07-05T08:46:25Z"},{"alias_kind":"pith_short_16","alias_value":"GIVMQGOLK3IRUZ6C","created_at":"2026-07-05T08:46:25Z"},{"alias_kind":"pith_short_8","alias_value":"GIVMQGOL","created_at":"2026-07-05T08:46:25Z"}],"graph_snapshots":[{"event_id":"sha256:a4e334f5cabd56a060a3c2ba0117fcca7eddcf4899484af08e7efb007011a3d5","target":"graph","created_at":"2026-07-05T08:46:25Z","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/2405.19883/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, from a theoretical lens, we aim to understand why large language model (LLM) empowered agents are able to solve decision-making problems in the physical world. To this end, consider a hierarchical reinforcement learning (RL) model where the LLM Planner and the Actor perform high-level task planning and low-level execution, respectively. Under this model, the LLM Planner navigates a partially observable Markov decision process (POMDP) by iteratively generating language-based subgoals via prompting. Under proper assumptions on the pretraining data, we prove that the pretrained LLM ","authors_text":"Fengzhuo Zhang, Jianliang He, Siyu Chen, Zhuoran Yang","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-30T09:42:54Z","title":"From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19883","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":"sha256:8aaf84f9e9bde047cc46d686582989f439403ce10098f62d5a22027709227df4","target":"record","created_at":"2026-07-05T08:46:25Z","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":"6ba050380609cb2be00fafd8e343c168ac7f9967086510773036601961ad96ea","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-30T09:42:54Z","title_canon_sha256":"5092a4b44a7bd6e73f278a82975105c8cfe50e65ec6624561df57e4c3ff9623a"},"schema_version":"1.0","source":{"id":"2405.19883","kind":"arxiv","version":2}},"canonical_sha256":"322ac819cb56d11a67c21d3a977c602e8048a2b83e796858e61531e429fca27b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"322ac819cb56d11a67c21d3a977c602e8048a2b83e796858e61531e429fca27b","first_computed_at":"2026-07-05T08:46:25.252937Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:46:25.252937Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fqI8mNBgOwGRCd3uLvAAbiiJXGsRxN06S8XcPPIE4LJJBkfrdl51w0ioWYuMvvP/3Whrz889rMe4vugGCLbHBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:46:25.253405Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.19883","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8aaf84f9e9bde047cc46d686582989f439403ce10098f62d5a22027709227df4","sha256:a4e334f5cabd56a060a3c2ba0117fcca7eddcf4899484af08e7efb007011a3d5"],"state_sha256":"7287a7eecc3a745bcbcf6f131a867607e53cfd24bb654ebe7c7aa2c6a5c44b70"}