{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:JWAFCZSEBMIFUW4Y7ZS3ZH6TST","short_pith_number":"pith:JWAFCZSE","canonical_record":{"source":{"id":"2306.14892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-26T17:58:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"df8f95ad9314113c76fe26118132ac6668422e6dec9863d8f3e774e11251d310","abstract_canon_sha256":"94139ee34686e8d902b4a5cb462ed76d14efbd4b269ed8c4f446b0d510e29a43"},"schema_version":"1.0"},"canonical_sha256":"4d805166440b105a5b98fe65bc9fd394e67abe32b6284c7eeb1a9f26a04d6feb","source":{"kind":"arxiv","id":"2306.14892","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.14892","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"arxiv_version","alias_value":"2306.14892v1","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.14892","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_12","alias_value":"JWAFCZSEBMIF","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_16","alias_value":"JWAFCZSEBMIFUW4Y","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_8","alias_value":"JWAFCZSE","created_at":"2026-07-05T06:24:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:JWAFCZSEBMIFUW4Y7ZS3ZH6TST","target":"record","payload":{"canonical_record":{"source":{"id":"2306.14892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-26T17:58:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"df8f95ad9314113c76fe26118132ac6668422e6dec9863d8f3e774e11251d310","abstract_canon_sha256":"94139ee34686e8d902b4a5cb462ed76d14efbd4b269ed8c4f446b0d510e29a43"},"schema_version":"1.0"},"canonical_sha256":"4d805166440b105a5b98fe65bc9fd394e67abe32b6284c7eeb1a9f26a04d6feb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:24:41.809670Z","signature_b64":"mc+cNPDxVn8xayBfv2Vw3XVuLzWkp8FYTZHYIIX1mSUOGZSAvSy5EFwM+Vv60QHR5vckcVLYt06wT/+UgSEgBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d805166440b105a5b98fe65bc9fd394e67abe32b6284c7eeb1a9f26a04d6feb","last_reissued_at":"2026-07-05T06:24:41.809294Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:24:41.809294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.14892","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:24:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n1sVIFC/X/+idbsai+Ht3/6wu/QdM46YSzmGe2UsU4gUBTPUntjysgQDqMacHf1IiiCyUfRlmQBC7zJaERSuCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T01:34:52.517627Z"},"content_sha256":"d97a90909ae0e29eca38928aed38e974f02099d5e11bf9354fae62f3741e51c9","schema_version":"1.0","event_id":"sha256:d97a90909ae0e29eca38928aed38e974f02099d5e11bf9354fae62f3741e51c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:JWAFCZSEBMIFUW4Y7ZS3ZH6TST","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Supervised Pretraining Can Learn In-Context Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Aldo Pacchiano, Annie Xie, Chelsea Finn, Emma Brunskill, Jonathan N. Lee, Ofir Nachum, Yash Chandak","submitted_at":"2023-06-26T17:58:50Z","abstract_excerpt":"Large transformer models trained on diverse datasets have shown a remarkable ability to learn in-context, achieving high few-shot performance on tasks they were not explicitly trained to solve. In this paper, we study the in-context learning capabilities of transformers in decision-making problems, i.e., reinforcement learning (RL) for bandits and Markov decision processes. To do so, we introduce and study Decision-Pretrained Transformer (DPT), a supervised pretraining method where the transformer predicts an optimal action given a query state and an in-context dataset of interactions, across "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.14892","kind":"arxiv","version":1},"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/2306.14892/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":"2026-07-05T06:24:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"odr5f+ly2UARKhrhjEhwcNJ4Z2S8aRWu84ICo/ZaZQdiI7CJMWRvm18wf8+H8oxi/Q3DiZNjEu+WgtgmGO/6BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T01:34:52.518124Z"},"content_sha256":"d324492d16d535d4e4b903fb1d17c7343743537bd95c28fec95b38e9043fb9dd","schema_version":"1.0","event_id":"sha256:d324492d16d535d4e4b903fb1d17c7343743537bd95c28fec95b38e9043fb9dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/bundle.json","state_url":"https://pith.science/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/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":"2026-08-15T01:34:52Z","links":{"resolver":"https://pith.science/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST","bundle":"https://pith.science/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/bundle.json","state":"https://pith.science/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JWAFCZSEBMIFUW4Y7ZS3ZH6TST/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JWAFCZSEBMIFUW4Y7ZS3ZH6TST","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":"94139ee34686e8d902b4a5cb462ed76d14efbd4b269ed8c4f446b0d510e29a43","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-26T17:58:50Z","title_canon_sha256":"df8f95ad9314113c76fe26118132ac6668422e6dec9863d8f3e774e11251d310"},"schema_version":"1.0","source":{"id":"2306.14892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.14892","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"arxiv_version","alias_value":"2306.14892v1","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.14892","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_12","alias_value":"JWAFCZSEBMIF","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_16","alias_value":"JWAFCZSEBMIFUW4Y","created_at":"2026-07-05T06:24:41Z"},{"alias_kind":"pith_short_8","alias_value":"JWAFCZSE","created_at":"2026-07-05T06:24:41Z"}],"graph_snapshots":[{"event_id":"sha256:d324492d16d535d4e4b903fb1d17c7343743537bd95c28fec95b38e9043fb9dd","target":"graph","created_at":"2026-07-05T06:24:41Z","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/2306.14892/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large transformer models trained on diverse datasets have shown a remarkable ability to learn in-context, achieving high few-shot performance on tasks they were not explicitly trained to solve. In this paper, we study the in-context learning capabilities of transformers in decision-making problems, i.e., reinforcement learning (RL) for bandits and Markov decision processes. To do so, we introduce and study Decision-Pretrained Transformer (DPT), a supervised pretraining method where the transformer predicts an optimal action given a query state and an in-context dataset of interactions, across ","authors_text":"Aldo Pacchiano, Annie Xie, Chelsea Finn, Emma Brunskill, Jonathan N. Lee, Ofir Nachum, Yash Chandak","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-26T17:58:50Z","title":"Supervised Pretraining Can Learn In-Context Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.14892","kind":"arxiv","version":1},"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:d97a90909ae0e29eca38928aed38e974f02099d5e11bf9354fae62f3741e51c9","target":"record","created_at":"2026-07-05T06:24:41Z","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":"94139ee34686e8d902b4a5cb462ed76d14efbd4b269ed8c4f446b0d510e29a43","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-26T17:58:50Z","title_canon_sha256":"df8f95ad9314113c76fe26118132ac6668422e6dec9863d8f3e774e11251d310"},"schema_version":"1.0","source":{"id":"2306.14892","kind":"arxiv","version":1}},"canonical_sha256":"4d805166440b105a5b98fe65bc9fd394e67abe32b6284c7eeb1a9f26a04d6feb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4d805166440b105a5b98fe65bc9fd394e67abe32b6284c7eeb1a9f26a04d6feb","first_computed_at":"2026-07-05T06:24:41.809294Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:24:41.809294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mc+cNPDxVn8xayBfv2Vw3XVuLzWkp8FYTZHYIIX1mSUOGZSAvSy5EFwM+Vv60QHR5vckcVLYt06wT/+UgSEgBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:24:41.809670Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.14892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d97a90909ae0e29eca38928aed38e974f02099d5e11bf9354fae62f3741e51c9","sha256:d324492d16d535d4e4b903fb1d17c7343743537bd95c28fec95b38e9043fb9dd"],"state_sha256":"6c4ea80098c6dbc3a47d71141d9a86ad9779accd3856a4435db00c62eeca346f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5+nx9+aRiQpbRlY8qIO/UfRq35t1xuxGLpaQv8zZ4uo4FhOKj1AOpzV5k5PD3KzbGnPDTret0D76iJossDlzCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T01:34:52.522445Z","bundle_sha256":"188720d006db94533047c633787494473b3bda7f2a25c139857747a825d26df5"}}