{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5TDPVRYRCVKAHI3CULJSOGWD2S","short_pith_number":"pith:5TDPVRYR","schema_version":"1.0","canonical_sha256":"ecc6fac711155403a362a2d3271ac3d4a85c6368c9514e7c89e33b0887b438cf","source":{"kind":"arxiv","id":"2402.18016","version":3},"attestation_state":"computed","paper":{"title":"User Decision Guidance with Selective Explanation Presentation from Explainable-AI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Seiji Yamada, Yosuke Fukuchi","submitted_at":"2024-02-28T03:21:25Z","abstract_excerpt":"This paper addresses the challenge of selecting explanations for XAI (Explainable AI)-based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in improving user decisions through XAI-generated explanations along with AI predictions, and the development of XAI made it possible to generate a variety of such explanations. However, how IDSSs should select explanations to enhance user decision-making remains an open question. This paper proposes X-Selector, a method for selectively presenting XAI explanations. It enables IDSSs to strategically guide users to an AI-suggested deci"},"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":"2402.18016","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-02-28T03:21:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"eb8b0ac191e555592b43540052e6e9706f8bff19079a775d1534d42bf1bb3ed9","abstract_canon_sha256":"97c16febd261c5f2b43d6671dc016c7da74c08ed6d7e04b20866130b76f42812"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:23:19.022256Z","signature_b64":"tjjeBEDr6mK0Ik8BoF3WySe8kScJHS94D06myKIA4D5Gc4oaf3/xIfViCQ6HNULQh+ijn01a39stMiNRbJweDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ecc6fac711155403a362a2d3271ac3d4a85c6368c9514e7c89e33b0887b438cf","last_reissued_at":"2026-07-05T08:23:19.021813Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:23:19.021813Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"User Decision Guidance with Selective Explanation Presentation from Explainable-AI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Seiji Yamada, Yosuke Fukuchi","submitted_at":"2024-02-28T03:21:25Z","abstract_excerpt":"This paper addresses the challenge of selecting explanations for XAI (Explainable AI)-based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in improving user decisions through XAI-generated explanations along with AI predictions, and the development of XAI made it possible to generate a variety of such explanations. However, how IDSSs should select explanations to enhance user decision-making remains an open question. This paper proposes X-Selector, a method for selectively presenting XAI explanations. It enables IDSSs to strategically guide users to an AI-suggested deci"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.18016","kind":"arxiv","version":3},"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/2402.18016/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":"2402.18016","created_at":"2026-07-05T08:23:19.021868+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.18016v3","created_at":"2026-07-05T08:23:19.021868+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.18016","created_at":"2026-07-05T08:23:19.021868+00:00"},{"alias_kind":"pith_short_12","alias_value":"5TDPVRYRCVKA","created_at":"2026-07-05T08:23:19.021868+00:00"},{"alias_kind":"pith_short_16","alias_value":"5TDPVRYRCVKAHI3C","created_at":"2026-07-05T08:23:19.021868+00:00"},{"alias_kind":"pith_short_8","alias_value":"5TDPVRYR","created_at":"2026-07-05T08:23:19.021868+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.16627","citing_title":"Engaging with AI: How Interface Design Shapes Human-AI Collaboration in High-Stakes Decision-Making","ref_index":53,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S","json":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S.json","graph_json":"https://pith.science/api/pith-number/5TDPVRYRCVKAHI3CULJSOGWD2S/graph.json","events_json":"https://pith.science/api/pith-number/5TDPVRYRCVKAHI3CULJSOGWD2S/events.json","paper":"https://pith.science/paper/5TDPVRYR"},"agent_actions":{"view_html":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S","download_json":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S.json","view_paper":"https://pith.science/paper/5TDPVRYR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.18016&json=true","fetch_graph":"https://pith.science/api/pith-number/5TDPVRYRCVKAHI3CULJSOGWD2S/graph.json","fetch_events":"https://pith.science/api/pith-number/5TDPVRYRCVKAHI3CULJSOGWD2S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S/action/storage_attestation","attest_author":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S/action/author_attestation","sign_citation":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S/action/citation_signature","submit_replication":"https://pith.science/pith/5TDPVRYRCVKAHI3CULJSOGWD2S/action/replication_record"}},"created_at":"2026-07-05T08:23:19.021868+00:00","updated_at":"2026-07-05T08:23:19.021868+00:00"}