{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QSFG7ET7Y7ISV2PF3WBOH5Z5EM","short_pith_number":"pith:QSFG7ET7","canonical_record":{"source":{"id":"2407.07086","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-07-09T17:57:15Z","cross_cats_sorted":[],"title_canon_sha256":"f3998ff955ef0ef25d6d22810c43f8af37077d7fabc106c7d20af7a5ed7fd6be","abstract_canon_sha256":"f29d77c2c6a5b0dadf91b0f53ba3ca92dbb946b5922ac76868acb7eb68b69829"},"schema_version":"1.0"},"canonical_sha256":"848a6f927fc7d12ae9e5dd82e3f73d23208af2787243964d08d815aed6e7b09d","source":{"kind":"arxiv","id":"2407.07086","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.07086","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2407.07086v2","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.07086","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"QSFG7ET7Y7IS","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"QSFG7ET7Y7ISV2PF","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"QSFG7ET7","created_at":"2026-07-05T09:47:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QSFG7ET7Y7ISV2PF3WBOH5Z5EM","target":"record","payload":{"canonical_record":{"source":{"id":"2407.07086","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-07-09T17:57:15Z","cross_cats_sorted":[],"title_canon_sha256":"f3998ff955ef0ef25d6d22810c43f8af37077d7fabc106c7d20af7a5ed7fd6be","abstract_canon_sha256":"f29d77c2c6a5b0dadf91b0f53ba3ca92dbb946b5922ac76868acb7eb68b69829"},"schema_version":"1.0"},"canonical_sha256":"848a6f927fc7d12ae9e5dd82e3f73d23208af2787243964d08d815aed6e7b09d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:47:55.750669Z","signature_b64":"F8/QGZ6PE+u+PbWdjeDsGcFTjGNdSayX90fGTx7tM5TwrfBuCCxzM7+t5EsGu+O4nKiIWNpbKh1WlFJ8GI/NCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"848a6f927fc7d12ae9e5dd82e3f73d23208af2787243964d08d815aed6e7b09d","last_reissued_at":"2026-07-05T09:47:55.750285Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:47:55.750285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.07086","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t8go+aXeFYbDwsdI7bOShKgLQtjxUSaztzfBQ6EHe6PkPjYAv5tSRWhZelA+NCO4FQaLZK7pHMlDkynZ0MgHBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:18:59.202920Z"},"content_sha256":"ac004bc8fa735b4503354bf5a0870c935e5d6a53285634ace6dc096bd2b96d8e","schema_version":"1.0","event_id":"sha256:ac004bc8fa735b4503354bf5a0870c935e5d6a53285634ace6dc096bd2b96d8e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QSFG7ET7Y7ISV2PF3WBOH5Z5EM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Agam Bhatia, Daniel LK Yamins, Logan Cross, Nick Haber, Violet Xiang","submitted_at":"2024-07-09T17:57:15Z","abstract_excerpt":"Multi-agent reinforcement learning (MARL) methods struggle with the non-stationarity of multi-agent systems and fail to adaptively learn online when tested with novel agents. Here, we leverage large language models (LLMs) to create an autonomous agent that can handle these challenges. Our agent, Hypothetical Minds, consists of a cognitively-inspired architecture, featuring modular components for perception, memory, and hierarchical planning over two levels of abstraction. We introduce the Theory of Mind module that scaffolds the high-level planning process by generating hypotheses about other "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.07086","kind":"arxiv","version":2},"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/2407.07086/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":"2026-07-05T09:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Nv5HoKyJi3V1Dfoc/rB31Oxx/Am0M39OA/kIdnZsMo9R0X9s5xmAMbNbpWq4lY/ICFwqfYhNnrAPGPs1eUIBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:18:59.203790Z"},"content_sha256":"7a98ff4930bd650e160aeb2f69849684673b38d0ab8cf8b447fc8a281a71ae14","schema_version":"1.0","event_id":"sha256:7a98ff4930bd650e160aeb2f69849684673b38d0ab8cf8b447fc8a281a71ae14"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/bundle.json","state_url":"https://pith.science/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/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":"2026-08-09T10:18:59Z","links":{"resolver":"https://pith.science/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM","bundle":"https://pith.science/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/bundle.json","state":"https://pith.science/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QSFG7ET7Y7ISV2PF3WBOH5Z5EM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QSFG7ET7Y7ISV2PF3WBOH5Z5EM","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":"f29d77c2c6a5b0dadf91b0f53ba3ca92dbb946b5922ac76868acb7eb68b69829","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-07-09T17:57:15Z","title_canon_sha256":"f3998ff955ef0ef25d6d22810c43f8af37077d7fabc106c7d20af7a5ed7fd6be"},"schema_version":"1.0","source":{"id":"2407.07086","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.07086","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2407.07086v2","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.07086","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"QSFG7ET7Y7IS","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"QSFG7ET7Y7ISV2PF","created_at":"2026-07-05T09:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"QSFG7ET7","created_at":"2026-07-05T09:47:55Z"}],"graph_snapshots":[{"event_id":"sha256:7a98ff4930bd650e160aeb2f69849684673b38d0ab8cf8b447fc8a281a71ae14","target":"graph","created_at":"2026-07-05T09:47:55Z","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/2407.07086/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-agent reinforcement learning (MARL) methods struggle with the non-stationarity of multi-agent systems and fail to adaptively learn online when tested with novel agents. Here, we leverage large language models (LLMs) to create an autonomous agent that can handle these challenges. Our agent, Hypothetical Minds, consists of a cognitively-inspired architecture, featuring modular components for perception, memory, and hierarchical planning over two levels of abstraction. We introduce the Theory of Mind module that scaffolds the high-level planning process by generating hypotheses about other ","authors_text":"Agam Bhatia, Daniel LK Yamins, Logan Cross, Nick Haber, Violet Xiang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-07-09T17:57:15Z","title":"Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.07086","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:ac004bc8fa735b4503354bf5a0870c935e5d6a53285634ace6dc096bd2b96d8e","target":"record","created_at":"2026-07-05T09:47:55Z","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":"f29d77c2c6a5b0dadf91b0f53ba3ca92dbb946b5922ac76868acb7eb68b69829","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-07-09T17:57:15Z","title_canon_sha256":"f3998ff955ef0ef25d6d22810c43f8af37077d7fabc106c7d20af7a5ed7fd6be"},"schema_version":"1.0","source":{"id":"2407.07086","kind":"arxiv","version":2}},"canonical_sha256":"848a6f927fc7d12ae9e5dd82e3f73d23208af2787243964d08d815aed6e7b09d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"848a6f927fc7d12ae9e5dd82e3f73d23208af2787243964d08d815aed6e7b09d","first_computed_at":"2026-07-05T09:47:55.750285Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:47:55.750285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F8/QGZ6PE+u+PbWdjeDsGcFTjGNdSayX90fGTx7tM5TwrfBuCCxzM7+t5EsGu+O4nKiIWNpbKh1WlFJ8GI/NCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:47:55.750669Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.07086","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac004bc8fa735b4503354bf5a0870c935e5d6a53285634ace6dc096bd2b96d8e","sha256:7a98ff4930bd650e160aeb2f69849684673b38d0ab8cf8b447fc8a281a71ae14"],"state_sha256":"19644c16566d744269cc4a0f96b3ebe233d358355e47cc1c29f2e16522657826"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4LNz9yXA/KMO4duxTkxpJQsmH90R2zpXkj+WJb1IgzQQ8Ixmbwp3vZ2pXQAYzHtLv/hIvwcAwdesu1aQhi8RDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:18:59.209288Z","bundle_sha256":"441bf6e572cb70905e8d62b8c96cc0458b387289bb941ce0bb3a60ec1788e177"}}