{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:OEDWWJMYQZO5PIVR6NK5MBNFWI","short_pith_number":"pith:OEDWWJMY","schema_version":"1.0","canonical_sha256":"71076b2598865dd7a2b1f355d605a5b23bfc52701bed6a747e2ba5d44f9fb5a2","source":{"kind":"arxiv","id":"2406.04374","version":2},"attestation_state":"computed","paper":{"title":"Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT","cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Guang Cheng, Xiaowu Dai, Yuantong Li","submitted_at":"2024-06-04T23:46:10Z","abstract_excerpt":"Recommender systems play a crucial role in internet economies by connecting users with relevant products. However, designing effective recommender systems faces the key challenges: the exploration-exploitation tradeoff in securing incentive to explore new products against user's self-interested preferences. While prior work addresses Bayesian Incentive Compatibility (BIC) in fixed-design linear bandits (Sellke & Slivkins, 2023), we tackle the challenge of stochastic user covariates sampled online. Unlike standard black-box reductions (Mansour et al., 2020), our two-stage framework exploits the"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2406.04374","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-06-04T23:46:10Z","cross_cats_sorted":["cs.GT","cs.LG","stat.ML"],"title_canon_sha256":"b6cdf4cc612535439b9b2d5063046a987b9bd0ac2f8b7dd6f771fa03b2d39516","abstract_canon_sha256":"0afbb56d706d14ae912c3c4da8decd2753b10d6444231849418a0c6c4d0178d6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:03:46.115632Z","signature_b64":"HJEygYscealto+yjkiKgSdNv2lW8jR/hJ6DwJfktFGSqkpWg5wXTsia5Qs3VSQX2vQhI6aJbopFPvse7qQv5Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71076b2598865dd7a2b1f355d605a5b23bfc52701bed6a747e2ba5d44f9fb5a2","last_reissued_at":"2026-05-26T02:03:46.115020Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:03:46.115020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT","cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Guang Cheng, Xiaowu Dai, Yuantong Li","submitted_at":"2024-06-04T23:46:10Z","abstract_excerpt":"Recommender systems play a crucial role in internet economies by connecting users with relevant products. However, designing effective recommender systems faces the key challenges: the exploration-exploitation tradeoff in securing incentive to explore new products against user's self-interested preferences. While prior work addresses Bayesian Incentive Compatibility (BIC) in fixed-design linear bandits (Sellke & Slivkins, 2023), we tackle the challenge of stochastic user covariates sampled online. Unlike standard black-box reductions (Mansour et al., 2020), our two-stage framework exploits the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04374","kind":"arxiv","version":2},"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/2406.04374/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2406.04374","created_at":"2026-05-26T02:03:46.115108+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.04374v2","created_at":"2026-05-26T02:03:46.115108+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04374","created_at":"2026-05-26T02:03:46.115108+00:00"},{"alias_kind":"pith_short_12","alias_value":"OEDWWJMYQZO5","created_at":"2026-05-26T02:03:46.115108+00:00"},{"alias_kind":"pith_short_16","alias_value":"OEDWWJMYQZO5PIVR","created_at":"2026-05-26T02:03:46.115108+00:00"},{"alias_kind":"pith_short_8","alias_value":"OEDWWJMY","created_at":"2026-05-26T02:03:46.115108+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI","json":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI.json","graph_json":"https://pith.science/api/pith-number/OEDWWJMYQZO5PIVR6NK5MBNFWI/graph.json","events_json":"https://pith.science/api/pith-number/OEDWWJMYQZO5PIVR6NK5MBNFWI/events.json","paper":"https://pith.science/paper/OEDWWJMY"},"agent_actions":{"view_html":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI","download_json":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI.json","view_paper":"https://pith.science/paper/OEDWWJMY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.04374&json=true","fetch_graph":"https://pith.science/api/pith-number/OEDWWJMYQZO5PIVR6NK5MBNFWI/graph.json","fetch_events":"https://pith.science/api/pith-number/OEDWWJMYQZO5PIVR6NK5MBNFWI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI/action/storage_attestation","attest_author":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI/action/author_attestation","sign_citation":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI/action/citation_signature","submit_replication":"https://pith.science/pith/OEDWWJMYQZO5PIVR6NK5MBNFWI/action/replication_record"}},"created_at":"2026-05-26T02:03:46.115108+00:00","updated_at":"2026-05-26T02:03:46.115108+00:00"}