{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:XWFJABMAIGCZBZI3WTOXLM7M3Y","short_pith_number":"pith:XWFJABMA","canonical_record":{"source":{"id":"2304.08487","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-17T17:59:32Z","cross_cats_sorted":["cs.AI","cs.CV","cs.RO"],"title_canon_sha256":"ec440fa4c1da7e7ced8da60ba3290efa56ba810cdb32733f2a4e18dbf593a218","abstract_canon_sha256":"6a16363983044e81209f76ba9e820953d4678e4f40bcbbd14e554604b1a3979c"},"schema_version":"1.0"},"canonical_sha256":"bd8a900580418590e51bb4dd75b3ecde16dabb2556af6c6afaf21be0a158111a","source":{"kind":"arxiv","id":"2304.08487","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.08487","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"arxiv_version","alias_value":"2304.08487v1","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.08487","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_12","alias_value":"XWFJABMAIGCZ","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_16","alias_value":"XWFJABMAIGCZBZI3","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_8","alias_value":"XWFJABMA","created_at":"2026-07-05T06:01:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:XWFJABMAIGCZBZI3WTOXLM7M3Y","target":"record","payload":{"canonical_record":{"source":{"id":"2304.08487","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-17T17:59:32Z","cross_cats_sorted":["cs.AI","cs.CV","cs.RO"],"title_canon_sha256":"ec440fa4c1da7e7ced8da60ba3290efa56ba810cdb32733f2a4e18dbf593a218","abstract_canon_sha256":"6a16363983044e81209f76ba9e820953d4678e4f40bcbbd14e554604b1a3979c"},"schema_version":"1.0"},"canonical_sha256":"bd8a900580418590e51bb4dd75b3ecde16dabb2556af6c6afaf21be0a158111a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:01:52.968844Z","signature_b64":"nF9y2SuJhbW25JpjPIOpJYAAfRQBN9SXiPgWKE6M7LY7jICCI09zTcsoFN9Ge8p0JUMMWmupc4vUFHrwLE/qBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd8a900580418590e51bb4dd75b3ecde16dabb2556af6c6afaf21be0a158111a","last_reissued_at":"2026-07-05T06:01:52.968387Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:01:52.968387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.08487","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":"2026-07-05T06:01:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rvEZWULOSBtxcGHEmf0anHEWJZ1RxVs1cv1lvE/QQmQwHMi00UIetGjXwrvso5Vin0v0L1jb2WSXKQuEeCuBAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:53:01.224395Z"},"content_sha256":"e216b4f9e91aa87f1f2b2d969e25fb3fb7c4f068ed971e2f89b47016c8a63057","schema_version":"1.0","event_id":"sha256:e216b4f9e91aa87f1f2b2d969e25fb3fb7c4f068ed971e2f89b47016c8a63057"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:XWFJABMAIGCZBZI3WTOXLM7M3Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hyper-Decision Transformer for Efficient Online Policy Adaptation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.RO"],"primary_cat":"cs.LG","authors_text":"Chuang Gan, Ding Zhao, Mengdi Xu, Shun Zhang, Yikang Shen, Yuchen Lu","submitted_at":"2023-04-17T17:59:32Z","abstract_excerpt":"Decision Transformers (DT) have demonstrated strong performances in offline reinforcement learning settings, but quickly adapting to unseen novel tasks remains challenging. To address this challenge, we propose a new framework, called Hyper-Decision Transformer (HDT), that can generalize to novel tasks from a handful of demonstrations in a data- and parameter-efficient manner. To achieve such a goal, we propose to augment the base DT with an adaptation module, whose parameters are initialized by a hyper-network. When encountering unseen tasks, the hyper-network takes a handful of demonstration"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.08487","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/2304.08487/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":"2026-07-05T06:01:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sosboWMjMeVh2BiMDSGzNcX8fVx+WJPT9cdFk2UIJhJj0yetzfQLtQA1T4p/vcW39GnUkjSymeeWUnrdnvfzBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:53:01.225172Z"},"content_sha256":"cb6de10e068ecd0563842a5c4e9a557969840acfb36ce23de37f228988ff28c5","schema_version":"1.0","event_id":"sha256:cb6de10e068ecd0563842a5c4e9a557969840acfb36ce23de37f228988ff28c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/bundle.json","state_url":"https://pith.science/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/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":"2026-08-05T19:53:01Z","links":{"resolver":"https://pith.science/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y","bundle":"https://pith.science/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/bundle.json","state":"https://pith.science/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XWFJABMAIGCZBZI3WTOXLM7M3Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XWFJABMAIGCZBZI3WTOXLM7M3Y","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":"6a16363983044e81209f76ba9e820953d4678e4f40bcbbd14e554604b1a3979c","cross_cats_sorted":["cs.AI","cs.CV","cs.RO"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-17T17:59:32Z","title_canon_sha256":"ec440fa4c1da7e7ced8da60ba3290efa56ba810cdb32733f2a4e18dbf593a218"},"schema_version":"1.0","source":{"id":"2304.08487","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.08487","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"arxiv_version","alias_value":"2304.08487v1","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.08487","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_12","alias_value":"XWFJABMAIGCZ","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_16","alias_value":"XWFJABMAIGCZBZI3","created_at":"2026-07-05T06:01:52Z"},{"alias_kind":"pith_short_8","alias_value":"XWFJABMA","created_at":"2026-07-05T06:01:52Z"}],"graph_snapshots":[{"event_id":"sha256:cb6de10e068ecd0563842a5c4e9a557969840acfb36ce23de37f228988ff28c5","target":"graph","created_at":"2026-07-05T06:01:52Z","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/2304.08487/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Decision Transformers (DT) have demonstrated strong performances in offline reinforcement learning settings, but quickly adapting to unseen novel tasks remains challenging. To address this challenge, we propose a new framework, called Hyper-Decision Transformer (HDT), that can generalize to novel tasks from a handful of demonstrations in a data- and parameter-efficient manner. To achieve such a goal, we propose to augment the base DT with an adaptation module, whose parameters are initialized by a hyper-network. When encountering unseen tasks, the hyper-network takes a handful of demonstration","authors_text":"Chuang Gan, Ding Zhao, Mengdi Xu, Shun Zhang, Yikang Shen, Yuchen Lu","cross_cats":["cs.AI","cs.CV","cs.RO"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-17T17:59:32Z","title":"Hyper-Decision Transformer for Efficient Online Policy Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.08487","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:e216b4f9e91aa87f1f2b2d969e25fb3fb7c4f068ed971e2f89b47016c8a63057","target":"record","created_at":"2026-07-05T06:01:52Z","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":"6a16363983044e81209f76ba9e820953d4678e4f40bcbbd14e554604b1a3979c","cross_cats_sorted":["cs.AI","cs.CV","cs.RO"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-17T17:59:32Z","title_canon_sha256":"ec440fa4c1da7e7ced8da60ba3290efa56ba810cdb32733f2a4e18dbf593a218"},"schema_version":"1.0","source":{"id":"2304.08487","kind":"arxiv","version":1}},"canonical_sha256":"bd8a900580418590e51bb4dd75b3ecde16dabb2556af6c6afaf21be0a158111a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd8a900580418590e51bb4dd75b3ecde16dabb2556af6c6afaf21be0a158111a","first_computed_at":"2026-07-05T06:01:52.968387Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:01:52.968387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nF9y2SuJhbW25JpjPIOpJYAAfRQBN9SXiPgWKE6M7LY7jICCI09zTcsoFN9Ge8p0JUMMWmupc4vUFHrwLE/qBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:01:52.968844Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.08487","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e216b4f9e91aa87f1f2b2d969e25fb3fb7c4f068ed971e2f89b47016c8a63057","sha256:cb6de10e068ecd0563842a5c4e9a557969840acfb36ce23de37f228988ff28c5"],"state_sha256":"f703f51111d57280431c507f14d48e1af909958a52e78cd247cb3c97d4657b03"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X3ezcpaeVgj3hehDZ1rGGwZCGVZoaTau9ohdA+E5hBMWjFTK9hzeg62qbj2C2XHuiiD0XHiJbms80E1+4gJ2Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:53:01.230537Z","bundle_sha256":"0f06e9721d0c07c07b2c93890a2ae38faf98917ed0fb1f2d751c53a1b2fc6181"}}