{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HI6A2X7TVF6YYZJRZWMSLWEE2G","short_pith_number":"pith:HI6A2X7T","canonical_record":{"source":{"id":"2403.17634","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-03-26T12:08:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0ad9a105d99c3c8615cb48623bcc7f786e22449254a22e41e09547075b437cb8","abstract_canon_sha256":"2f95e060cdd0917b76654fbbe0771ff94f48eeed1c397c6db6f8106fffdad7c1"},"schema_version":"1.0"},"canonical_sha256":"3a3c0d5ff3a97d8c6531cd9925d884d1809b603e122770370059e6cfafde3f73","source":{"kind":"arxiv","id":"2403.17634","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.17634","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"arxiv_version","alias_value":"2403.17634v1","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.17634","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_12","alias_value":"HI6A2X7TVF6Y","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_16","alias_value":"HI6A2X7TVF6YYZJR","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_8","alias_value":"HI6A2X7T","created_at":"2026-07-05T08:00:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HI6A2X7TVF6YYZJRZWMSLWEE2G","target":"record","payload":{"canonical_record":{"source":{"id":"2403.17634","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-03-26T12:08:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0ad9a105d99c3c8615cb48623bcc7f786e22449254a22e41e09547075b437cb8","abstract_canon_sha256":"2f95e060cdd0917b76654fbbe0771ff94f48eeed1c397c6db6f8106fffdad7c1"},"schema_version":"1.0"},"canonical_sha256":"3a3c0d5ff3a97d8c6531cd9925d884d1809b603e122770370059e6cfafde3f73","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:00:53.723894Z","signature_b64":"AsPqaj8mgiT0zDsHZkExgIVMX7sqXjbaPfJV0zXkK2pTiyUkSMwHROKX0rOQHQLs7oseHOal7UpnKIa0i+vgAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a3c0d5ff3a97d8c6531cd9925d884d1809b603e122770370059e6cfafde3f73","last_reissued_at":"2026-07-05T08:00:53.723492Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:00:53.723492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.17634","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":"2026-07-05T08:00:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p7F22huKxxgeBWFU9I4IeFZJBiY8LE6hE02pQ2dtQrj7uX4ux5SL3qghWWl2rRTTbrN4HLH5kW15Zj80ZnMFDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:13:12.920980Z"},"content_sha256":"4d7512e46bd8bfbf8dc3446006b96f1d1034d4da3eb0734c052caea52eb4f4c1","schema_version":"1.0","event_id":"sha256:4d7512e46bd8bfbf8dc3446006b96f1d1034d4da3eb0734c052caea52eb4f4c1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HI6A2X7TVF6YYZJRZWMSLWEE2G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Lina Yao, Siyu Wang, Xiaocong Chen","submitted_at":"2024-03-26T12:08:58Z","abstract_excerpt":"Reinforcement Learning-based Recommender Systems (RLRS) have shown promise across a spectrum of applications, from e-commerce platforms to streaming services. Yet, they grapple with challenges, notably in crafting reward functions and harnessing large pre-existing datasets within the RL framework. Recent advancements in offline RLRS provide a solution for how to address these two challenges. However, existing methods mainly rely on the transformer architecture, which, as sequence lengths increase, can introduce challenges associated with computational resources and training costs. Additionally"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.17634","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/2403.17634/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":"2026-07-05T08:00:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BScOdJogksdUrBPGHOjC3rMOWJNEEaHWEnOW2HZRIfT+svndShBdrj3ujMLV/v4gWV4Tqnb4e/pLG67o61r8AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:13:12.921385Z"},"content_sha256":"6ef4ea0273b8591413c250c8a4b7c6e6b3d3c3bab06df76a7d0ea7604d13ab2b","schema_version":"1.0","event_id":"sha256:6ef4ea0273b8591413c250c8a4b7c6e6b3d3c3bab06df76a7d0ea7604d13ab2b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/bundle.json","state_url":"https://pith.science/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/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":"2026-07-07T07:13:12Z","links":{"resolver":"https://pith.science/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G","bundle":"https://pith.science/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/bundle.json","state":"https://pith.science/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HI6A2X7TVF6YYZJRZWMSLWEE2G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HI6A2X7TVF6YYZJRZWMSLWEE2G","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":"2f95e060cdd0917b76654fbbe0771ff94f48eeed1c397c6db6f8106fffdad7c1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-03-26T12:08:58Z","title_canon_sha256":"0ad9a105d99c3c8615cb48623bcc7f786e22449254a22e41e09547075b437cb8"},"schema_version":"1.0","source":{"id":"2403.17634","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.17634","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"arxiv_version","alias_value":"2403.17634v1","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.17634","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_12","alias_value":"HI6A2X7TVF6Y","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_16","alias_value":"HI6A2X7TVF6YYZJR","created_at":"2026-07-05T08:00:53Z"},{"alias_kind":"pith_short_8","alias_value":"HI6A2X7T","created_at":"2026-07-05T08:00:53Z"}],"graph_snapshots":[{"event_id":"sha256:6ef4ea0273b8591413c250c8a4b7c6e6b3d3c3bab06df76a7d0ea7604d13ab2b","target":"graph","created_at":"2026-07-05T08:00:53Z","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/2403.17634/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement Learning-based Recommender Systems (RLRS) have shown promise across a spectrum of applications, from e-commerce platforms to streaming services. Yet, they grapple with challenges, notably in crafting reward functions and harnessing large pre-existing datasets within the RL framework. Recent advancements in offline RLRS provide a solution for how to address these two challenges. However, existing methods mainly rely on the transformer architecture, which, as sequence lengths increase, can introduce challenges associated with computational resources and training costs. Additionally","authors_text":"Lina Yao, Siyu Wang, Xiaocong Chen","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-03-26T12:08:58Z","title":"Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.17634","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":"sha256:4d7512e46bd8bfbf8dc3446006b96f1d1034d4da3eb0734c052caea52eb4f4c1","target":"record","created_at":"2026-07-05T08:00:53Z","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":"2f95e060cdd0917b76654fbbe0771ff94f48eeed1c397c6db6f8106fffdad7c1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-03-26T12:08:58Z","title_canon_sha256":"0ad9a105d99c3c8615cb48623bcc7f786e22449254a22e41e09547075b437cb8"},"schema_version":"1.0","source":{"id":"2403.17634","kind":"arxiv","version":1}},"canonical_sha256":"3a3c0d5ff3a97d8c6531cd9925d884d1809b603e122770370059e6cfafde3f73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a3c0d5ff3a97d8c6531cd9925d884d1809b603e122770370059e6cfafde3f73","first_computed_at":"2026-07-05T08:00:53.723492Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:00:53.723492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AsPqaj8mgiT0zDsHZkExgIVMX7sqXjbaPfJV0zXkK2pTiyUkSMwHROKX0rOQHQLs7oseHOal7UpnKIa0i+vgAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:00:53.723894Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.17634","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d7512e46bd8bfbf8dc3446006b96f1d1034d4da3eb0734c052caea52eb4f4c1","sha256:6ef4ea0273b8591413c250c8a4b7c6e6b3d3c3bab06df76a7d0ea7604d13ab2b"],"state_sha256":"78d35497f8a059f885a1c7b5739542693c88a46db95e2886abc70b138110d7e8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O44g++dS/+Gv6vdeSc2vhKW8bvo5LEnqhUwKY70Qp7Nfg2ZGqUI0+M6sTAC850szfWrRliEVxxGoWZWuRK5uAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T07:13:12.923781Z","bundle_sha256":"ba2fe08b1bd1c86ec3722561ab40cfce4b63978d27c4618ac87acf307d6e7c96"}}