{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LJP2EZDOUKAUYCWKGQC23A5ZQH","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":"a1d97eeb62fbb564eaa81ec590ec6979d03805ec50127f19e9c1f07b76e41e5a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-15T22:20:39Z","title_canon_sha256":"10d8c5311b08b907ae445a306e6bd68357043d0d045ce164f5a662fead920462"},"schema_version":"1.0","source":{"id":"2310.09971","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.09971","created_at":"2026-07-05T07:40:02Z"},{"alias_kind":"arxiv_version","alias_value":"2310.09971v4","created_at":"2026-07-05T07:40:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.09971","created_at":"2026-07-05T07:40:02Z"},{"alias_kind":"pith_short_12","alias_value":"LJP2EZDOUKAU","created_at":"2026-07-05T07:40:02Z"},{"alias_kind":"pith_short_16","alias_value":"LJP2EZDOUKAUYCWK","created_at":"2026-07-05T07:40:02Z"},{"alias_kind":"pith_short_8","alias_value":"LJP2EZDO","created_at":"2026-07-05T07:40:02Z"}],"graph_snapshots":[{"event_id":"sha256:8e196d9d5d7baa1995ba42f689fba15b08ab4352c65545fbb7f2ffed8ab7ad55","target":"graph","created_at":"2026-07-05T07:40:02Z","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/2310.09971/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce AMAGO, an in-context Reinforcement Learning (RL) agent that uses sequence models to tackle the challenges of generalization, long-term memory, and meta-learning. Recent works have shown that off-policy learning can make in-context RL with recurrent policies viable. Nonetheless, these approaches require extensive tuning and limit scalability by creating key bottlenecks in agents' memory capacity, planning horizon, and model size. AMAGO revisits and redesigns the off-policy in-context approach to successfully train long-sequence Transformers over entire rollouts in parallel with end","authors_text":"Jake Grigsby, Linxi Fan, Yuke Zhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-15T22:20:39Z","title":"AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.09971","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":"sha256:247aceabcb54b5c59d8286d06311575549544a6923e2718a2161d41f360010a0","target":"record","created_at":"2026-07-05T07:40:02Z","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":"a1d97eeb62fbb564eaa81ec590ec6979d03805ec50127f19e9c1f07b76e41e5a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-15T22:20:39Z","title_canon_sha256":"10d8c5311b08b907ae445a306e6bd68357043d0d045ce164f5a662fead920462"},"schema_version":"1.0","source":{"id":"2310.09971","kind":"arxiv","version":4}},"canonical_sha256":"5a5fa2646ea2814c0aca3405ad83b981f46522190f2e294a82eb5684a2caeaf5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a5fa2646ea2814c0aca3405ad83b981f46522190f2e294a82eb5684a2caeaf5","first_computed_at":"2026-07-05T07:40:02.796999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:40:02.796999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k4OM8wQJUsyJ7GexVbkT4ehyh/M1AeGP7RRvYbOt1abHAPHRXu6pc6egdi1K2v5Xr7MVPW4Mip4iw3wgZjgiDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:40:02.797432Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.09971","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:247aceabcb54b5c59d8286d06311575549544a6923e2718a2161d41f360010a0","sha256:8e196d9d5d7baa1995ba42f689fba15b08ab4352c65545fbb7f2ffed8ab7ad55"],"state_sha256":"2ca7be1ba25fa350f4ed19f68d7dfbdd85aafdf2526731adbd0ccce978dd254d"}