{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3ZFFFB7TPBHGVGJUB4HQDRFZ7Z","short_pith_number":"pith:3ZFFFB7T","canonical_record":{"source":{"id":"2501.19318","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-31T17:15:33Z","cross_cats_sorted":[],"title_canon_sha256":"f6ac24781f3b13b15bf289fbfa3a7732de66b51d63d9c673eb4c1b0463140a9f","abstract_canon_sha256":"933e071884390359088344b536e7deacace67f1ef9167094d40a4f4a11fea59d"},"schema_version":"1.0"},"canonical_sha256":"de4a5287f3784e6a99340f0f01c4b9fe6583b651090abc22faff1ed4bbd79d5b","source":{"kind":"arxiv","id":"2501.19318","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.19318","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2501.19318v4","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.19318","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"3ZFFFB7TPBHG","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"3ZFFFB7TPBHGVGJU","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"3ZFFFB7T","created_at":"2026-07-05T11:14:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3ZFFFB7TPBHGVGJUB4HQDRFZ7Z","target":"record","payload":{"canonical_record":{"source":{"id":"2501.19318","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-31T17:15:33Z","cross_cats_sorted":[],"title_canon_sha256":"f6ac24781f3b13b15bf289fbfa3a7732de66b51d63d9c673eb4c1b0463140a9f","abstract_canon_sha256":"933e071884390359088344b536e7deacace67f1ef9167094d40a4f4a11fea59d"},"schema_version":"1.0"},"canonical_sha256":"de4a5287f3784e6a99340f0f01c4b9fe6583b651090abc22faff1ed4bbd79d5b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:53.195950Z","signature_b64":"bf3pXP/sXKv6EoKL3Qca/3pQoIZtflm3XddY2dvKVGztWAtinqUsvYkWEuMAsZXdPPd/YMMDPJSOzgn0mZUvBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de4a5287f3784e6a99340f0f01c4b9fe6583b651090abc22faff1ed4bbd79d5b","last_reissued_at":"2026-07-05T11:14:53.195494Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:53.195494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.19318","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"05F6zGc2bnN83MTPkPxQ43HEyDkaKlpX6QPpKbdOg0rHr2I8X3fn4nX4QbmamgoZozS1GfVTRS6dz7Na5k66CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:32:17.588295Z"},"content_sha256":"37c0684d677bba20588d7ab62e36d11fbde91ce1a12bd0c2aae2fb932a786b19","schema_version":"1.0","event_id":"sha256:37c0684d677bba20588d7ab62e36d11fbde91ce1a12bd0c2aae2fb932a786b19"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3ZFFFB7TPBHGVGJUB4HQDRFZ7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MINDSTORES: Memory-Informed Neural Decision Synthesis for Task-Oriented Reinforcement in Embodied Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Aditya Tiwari, Anirudh Chari, Brian Zhou, Richard Lian, Suraj Reddy","submitted_at":"2025-01-31T17:15:33Z","abstract_excerpt":"While large language models (LLMs) have shown promising capabilities as zero-shot planners for embodied agents, their inability to learn from experience and build persistent mental models limits their robustness in complex open-world environments like Minecraft. We introduce MINDSTORES, an experience-augmented planning framework that enables embodied agents to build and leverage mental models through natural interaction with their environment. Drawing inspiration from how humans construct and refine cognitive mental models, our approach extends existing zero-shot LLM planning by maintaining a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.19318","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.19318/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u7CXtAVRvH/ProW81t9r6SNISlLOuFEKdwaGbzZUvWh9v8TksF4703IVXjfCyjNpkiOrww9+ryD0Vpla9q1JAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:32:17.589306Z"},"content_sha256":"fbf8cc9c7dedcfba12aa358e6e6c518dbc6542c185cbb10feb4889e8ad9c21a9","schema_version":"1.0","event_id":"sha256:fbf8cc9c7dedcfba12aa358e6e6c518dbc6542c185cbb10feb4889e8ad9c21a9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/bundle.json","state_url":"https://pith.science/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T09:32:17Z","links":{"resolver":"https://pith.science/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z","bundle":"https://pith.science/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/bundle.json","state":"https://pith.science/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3ZFFFB7TPBHGVGJUB4HQDRFZ7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3ZFFFB7TPBHGVGJUB4HQDRFZ7Z","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":"933e071884390359088344b536e7deacace67f1ef9167094d40a4f4a11fea59d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-31T17:15:33Z","title_canon_sha256":"f6ac24781f3b13b15bf289fbfa3a7732de66b51d63d9c673eb4c1b0463140a9f"},"schema_version":"1.0","source":{"id":"2501.19318","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.19318","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2501.19318v4","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.19318","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"3ZFFFB7TPBHG","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"3ZFFFB7TPBHGVGJU","created_at":"2026-07-05T11:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"3ZFFFB7T","created_at":"2026-07-05T11:14:53Z"}],"graph_snapshots":[{"event_id":"sha256:fbf8cc9c7dedcfba12aa358e6e6c518dbc6542c185cbb10feb4889e8ad9c21a9","target":"graph","created_at":"2026-07-05T11:14:53Z","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/2501.19318/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While large language models (LLMs) have shown promising capabilities as zero-shot planners for embodied agents, their inability to learn from experience and build persistent mental models limits their robustness in complex open-world environments like Minecraft. We introduce MINDSTORES, an experience-augmented planning framework that enables embodied agents to build and leverage mental models through natural interaction with their environment. Drawing inspiration from how humans construct and refine cognitive mental models, our approach extends existing zero-shot LLM planning by maintaining a ","authors_text":"Aditya Tiwari, Anirudh Chari, Brian Zhou, Richard Lian, Suraj Reddy","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-31T17:15:33Z","title":"MINDSTORES: Memory-Informed Neural Decision Synthesis for Task-Oriented Reinforcement in Embodied Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.19318","kind":"arxiv","version":4},"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":"sha256:37c0684d677bba20588d7ab62e36d11fbde91ce1a12bd0c2aae2fb932a786b19","target":"record","created_at":"2026-07-05T11:14:53Z","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":"933e071884390359088344b536e7deacace67f1ef9167094d40a4f4a11fea59d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-31T17:15:33Z","title_canon_sha256":"f6ac24781f3b13b15bf289fbfa3a7732de66b51d63d9c673eb4c1b0463140a9f"},"schema_version":"1.0","source":{"id":"2501.19318","kind":"arxiv","version":4}},"canonical_sha256":"de4a5287f3784e6a99340f0f01c4b9fe6583b651090abc22faff1ed4bbd79d5b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"de4a5287f3784e6a99340f0f01c4b9fe6583b651090abc22faff1ed4bbd79d5b","first_computed_at":"2026-07-05T11:14:53.195494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:14:53.195494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bf3pXP/sXKv6EoKL3Qca/3pQoIZtflm3XddY2dvKVGztWAtinqUsvYkWEuMAsZXdPPd/YMMDPJSOzgn0mZUvBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:14:53.195950Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.19318","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37c0684d677bba20588d7ab62e36d11fbde91ce1a12bd0c2aae2fb932a786b19","sha256:fbf8cc9c7dedcfba12aa358e6e6c518dbc6542c185cbb10feb4889e8ad9c21a9"],"state_sha256":"f6d10c61f881ba5e717e2bed18cb257349854d0fc1b46b13ce335449eac87f41"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/6WUZ5U5KzEod0kZzX2gqa+iX8TWmKVFqCe/24mCL6EfDMQAQJaMBWyIy1/CUrNKWA/S9dCs++ipTLug/1sXAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:32:17.596976Z","bundle_sha256":"612712c329412cb36c0e45f4eaa36080c8e725dc0f577d25242163c6fc74582b"}}