{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:AM3KFUZRIWNR27Y26A2JVSOCWO","short_pith_number":"pith:AM3KFUZR","schema_version":"1.0","canonical_sha256":"0336a2d331459b1d7f1af0349ac9c2b3bd7a5dfbe84526137e6b135c53218da4","source":{"kind":"arxiv","id":"2307.07909","version":3},"attestation_state":"computed","paper":{"title":"Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ashish Kapoor, Ratnesh Madaan, Rogerio Bonatti, Ruijie Zheng, Sai Vemprala, Shuang Ma, Shuhang Chen, Yanchao Sun, Yao Wei, Zhongjie Ba","submitted_at":"2023-07-16T00:34:12Z","abstract_excerpt":"We introduce DualMind, a generalist agent designed to tackle various decision-making tasks that addresses challenges posed by current methods, such as overfitting behaviors and dependence on task-specific fine-tuning. DualMind uses a novel \"Dual-phase\" training strategy that emulates how humans learn to act in the world. The model first learns fundamental common knowledge through a self-supervised objective tailored for control tasks and then learns how to make decisions based on different contexts through imitating behaviors conditioned on given prompts. DualMind can handle tasks across domai"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.07909","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-07-16T00:34:12Z","cross_cats_sorted":[],"title_canon_sha256":"b61b49874c2dbdd3c16cf55f511af48dd8948721e261c353c711ad7e6d94e466","abstract_canon_sha256":"981bf88f9ebf3b768de676ef07931d9ba25930442f0785ee8b5fd30de3a7bd16"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:58:41.322990Z","signature_b64":"ln60LvVEOcNVJLmKC5IaUg+fLagLLLLZ7hJRaxrAzafs02a5qPuAcXoopSKU87qbHNgFD+0zwbTyKni49cSUBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0336a2d331459b1d7f1af0349ac9c2b3bd7a5dfbe84526137e6b135c53218da4","last_reissued_at":"2026-07-05T06:58:41.322427Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:58:41.322427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ashish Kapoor, Ratnesh Madaan, Rogerio Bonatti, Ruijie Zheng, Sai Vemprala, Shuang Ma, Shuhang Chen, Yanchao Sun, Yao Wei, Zhongjie Ba","submitted_at":"2023-07-16T00:34:12Z","abstract_excerpt":"We introduce DualMind, a generalist agent designed to tackle various decision-making tasks that addresses challenges posed by current methods, such as overfitting behaviors and dependence on task-specific fine-tuning. DualMind uses a novel \"Dual-phase\" training strategy that emulates how humans learn to act in the world. The model first learns fundamental common knowledge through a self-supervised objective tailored for control tasks and then learns how to make decisions based on different contexts through imitating behaviors conditioned on given prompts. DualMind can handle tasks across domai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07909","kind":"arxiv","version":3},"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/2307.07909/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.07909","created_at":"2026-07-05T06:58:41.322499+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.07909v3","created_at":"2026-07-05T06:58:41.322499+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07909","created_at":"2026-07-05T06:58:41.322499+00:00"},{"alias_kind":"pith_short_12","alias_value":"AM3KFUZRIWNR","created_at":"2026-07-05T06:58:41.322499+00:00"},{"alias_kind":"pith_short_16","alias_value":"AM3KFUZRIWNR27Y2","created_at":"2026-07-05T06:58:41.322499+00:00"},{"alias_kind":"pith_short_8","alias_value":"AM3KFUZR","created_at":"2026-07-05T06:58:41.322499+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO","json":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO.json","graph_json":"https://pith.science/api/pith-number/AM3KFUZRIWNR27Y26A2JVSOCWO/graph.json","events_json":"https://pith.science/api/pith-number/AM3KFUZRIWNR27Y26A2JVSOCWO/events.json","paper":"https://pith.science/paper/AM3KFUZR"},"agent_actions":{"view_html":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO","download_json":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO.json","view_paper":"https://pith.science/paper/AM3KFUZR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.07909&json=true","fetch_graph":"https://pith.science/api/pith-number/AM3KFUZRIWNR27Y26A2JVSOCWO/graph.json","fetch_events":"https://pith.science/api/pith-number/AM3KFUZRIWNR27Y26A2JVSOCWO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO/action/storage_attestation","attest_author":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO/action/author_attestation","sign_citation":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO/action/citation_signature","submit_replication":"https://pith.science/pith/AM3KFUZRIWNR27Y26A2JVSOCWO/action/replication_record"}},"created_at":"2026-07-05T06:58:41.322499+00:00","updated_at":"2026-07-05T06:58:41.322499+00:00"}