{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:Q4UFRSKUERLJIWBPWXS5R26F42","short_pith_number":"pith:Q4UFRSKU","canonical_record":{"source":{"id":"2004.06651","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2020-04-14T16:46:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"edbc7b27949f78ba1c549947752fd9460e56c265229d45609d44e5a35a367ed6","abstract_canon_sha256":"85312448ab7ccecc4beb303dcb9ef82e7da31efedf8168b532aabb11a422024c"},"schema_version":"1.0"},"canonical_sha256":"872858c954245694582fb5e5d8ebc5e6b62819d59890d3f96cc15909e8f95678","source":{"kind":"arxiv","id":"2004.06651","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.06651","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"arxiv_version","alias_value":"2004.06651v4","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.06651","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_12","alias_value":"Q4UFRSKUERLJ","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_16","alias_value":"Q4UFRSKUERLJIWBP","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_8","alias_value":"Q4UFRSKU","created_at":"2026-07-05T03:24:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:Q4UFRSKUERLJIWBPWXS5R26F42","target":"record","payload":{"canonical_record":{"source":{"id":"2004.06651","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2020-04-14T16:46:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"edbc7b27949f78ba1c549947752fd9460e56c265229d45609d44e5a35a367ed6","abstract_canon_sha256":"85312448ab7ccecc4beb303dcb9ef82e7da31efedf8168b532aabb11a422024c"},"schema_version":"1.0"},"canonical_sha256":"872858c954245694582fb5e5d8ebc5e6b62819d59890d3f96cc15909e8f95678","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:06.334521Z","signature_b64":"AVhtPhTSLn9Meiq+HtehKYEobNbIsahUy0ddnTWazwb+r+BSCTiAMcEtpB+zlhrOL/SMHw1AzstGHiyCv+K1CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"872858c954245694582fb5e5d8ebc5e6b62819d59890d3f96cc15909e8f95678","last_reissued_at":"2026-07-05T03:24:06.334106Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:06.334106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.06651","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:24:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h/XtpY2D+DHbda3I0bWlia0rKb/hfseTmztVm4dJKd+sks8A/Hvzo3pRedAixMGcU09khlAm1RUl7x1ZnmooAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T19:06:13.879827Z"},"content_sha256":"92ea449d16706461904ce01d0900f70fad13002e025253a97b02ffc3d2267690","schema_version":"1.0","event_id":"sha256:92ea449d16706461904ce01d0900f70fad13002e025253a97b02ffc3d2267690"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:Q4UFRSKUERLJIWBPWXS5R26F42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Text-based Deep Reinforcement Learning Framework for Interactive Recommendation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Chaoyang Wang, Guohui Li, Jianjun Li, Peng Pan, Zhiqiang Guo","submitted_at":"2020-04-14T16:46:01Z","abstract_excerpt":"Due to its nature of learning from dynamic interactions and planning for long-run performance, reinforcement learning (RL) recently has received much attention in interactive recommender systems (IRSs). IRSs usually face the large discrete action space problem, which makes most of the existing RL-based recommendation methods inefficient. Moreover, data sparsity is another challenging problem that most IRSs are confronted with. While the textual information like reviews and descriptions is less sensitive to sparsity, existing RL-based recommendation methods either neglect or are not suitable fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.06651","kind":"arxiv","version":4},"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/2004.06651/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":"2026-07-05T03:24:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ODbb7KAjzcHQtDif6eUIQ+FO1XXeOdfvi8qHFzAPsO22UYYupUtyz6kT7b7V/I7BaLNsFc3HqDPiO4oQBuZ6Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T19:06:13.880320Z"},"content_sha256":"600f0ed783e67da3ad855635a6a4d25cb156538e723a98756ad47e75e6037d8c","schema_version":"1.0","event_id":"sha256:600f0ed783e67da3ad855635a6a4d25cb156538e723a98756ad47e75e6037d8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q4UFRSKUERLJIWBPWXS5R26F42/bundle.json","state_url":"https://pith.science/pith/Q4UFRSKUERLJIWBPWXS5R26F42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q4UFRSKUERLJIWBPWXS5R26F42/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":"2026-08-22T19:06:13Z","links":{"resolver":"https://pith.science/pith/Q4UFRSKUERLJIWBPWXS5R26F42","bundle":"https://pith.science/pith/Q4UFRSKUERLJIWBPWXS5R26F42/bundle.json","state":"https://pith.science/pith/Q4UFRSKUERLJIWBPWXS5R26F42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q4UFRSKUERLJIWBPWXS5R26F42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:Q4UFRSKUERLJIWBPWXS5R26F42","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":"85312448ab7ccecc4beb303dcb9ef82e7da31efedf8168b532aabb11a422024c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2020-04-14T16:46:01Z","title_canon_sha256":"edbc7b27949f78ba1c549947752fd9460e56c265229d45609d44e5a35a367ed6"},"schema_version":"1.0","source":{"id":"2004.06651","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.06651","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"arxiv_version","alias_value":"2004.06651v4","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.06651","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_12","alias_value":"Q4UFRSKUERLJ","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_16","alias_value":"Q4UFRSKUERLJIWBP","created_at":"2026-07-05T03:24:06Z"},{"alias_kind":"pith_short_8","alias_value":"Q4UFRSKU","created_at":"2026-07-05T03:24:06Z"}],"graph_snapshots":[{"event_id":"sha256:600f0ed783e67da3ad855635a6a4d25cb156538e723a98756ad47e75e6037d8c","target":"graph","created_at":"2026-07-05T03:24:06Z","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/2004.06651/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Due to its nature of learning from dynamic interactions and planning for long-run performance, reinforcement learning (RL) recently has received much attention in interactive recommender systems (IRSs). IRSs usually face the large discrete action space problem, which makes most of the existing RL-based recommendation methods inefficient. Moreover, data sparsity is another challenging problem that most IRSs are confronted with. While the textual information like reviews and descriptions is less sensitive to sparsity, existing RL-based recommendation methods either neglect or are not suitable fo","authors_text":"Chaoyang Wang, Guohui Li, Jianjun Li, Peng Pan, Zhiqiang Guo","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2020-04-14T16:46:01Z","title":"A Text-based Deep Reinforcement Learning Framework for Interactive Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.06651","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":"sha256:92ea449d16706461904ce01d0900f70fad13002e025253a97b02ffc3d2267690","target":"record","created_at":"2026-07-05T03:24:06Z","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":"85312448ab7ccecc4beb303dcb9ef82e7da31efedf8168b532aabb11a422024c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2020-04-14T16:46:01Z","title_canon_sha256":"edbc7b27949f78ba1c549947752fd9460e56c265229d45609d44e5a35a367ed6"},"schema_version":"1.0","source":{"id":"2004.06651","kind":"arxiv","version":4}},"canonical_sha256":"872858c954245694582fb5e5d8ebc5e6b62819d59890d3f96cc15909e8f95678","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"872858c954245694582fb5e5d8ebc5e6b62819d59890d3f96cc15909e8f95678","first_computed_at":"2026-07-05T03:24:06.334106Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:24:06.334106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AVhtPhTSLn9Meiq+HtehKYEobNbIsahUy0ddnTWazwb+r+BSCTiAMcEtpB+zlhrOL/SMHw1AzstGHiyCv+K1CA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:24:06.334521Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.06651","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:92ea449d16706461904ce01d0900f70fad13002e025253a97b02ffc3d2267690","sha256:600f0ed783e67da3ad855635a6a4d25cb156538e723a98756ad47e75e6037d8c"],"state_sha256":"b0833e9163be4e0778067ff1ddf88876cc6a91a9eb87ea7000bc1d102fe39842"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HIb5QvMzrj8l16nI8S+41KiV8wiz76zoT5sq5rZPmxP89LuasBCk5IVHJ12Gr9fgLeVCu1a66lNq41eT+/J9Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T19:06:13.885286Z","bundle_sha256":"158b1c8987acaeb40921be9bdb719fa79681c7c27be4f17f904c057dd11ef2fe"}}