{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:GLP7YSE7NYTIIAQFUGXIMJRR6C","short_pith_number":"pith:GLP7YSE7","schema_version":"1.0","canonical_sha256":"32dffc489f6e26840205a1ae862631f0a6145cb69080d13980e0c62fa394d610","source":{"kind":"arxiv","id":"2201.05176","version":1},"attestation_state":"computed","paper":{"title":"Neural Approaches to Conversational Information Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Chenyan Xiong, Jianfeng Gao, Nick Craswell, Paul Bennett","submitted_at":"2022-01-13T19:04:59Z","abstract_excerpt":"A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or written form. Recent progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. As a result, we have witnesse"},"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":"2201.05176","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2022-01-13T19:04:59Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"c68663275380142d58ef289e3c69c0cc09bc124ece077f50d34ae7a41a9016ee","abstract_canon_sha256":"bfc6e8d75ecd013b20782b797df6253ed0728482d290d45f2a6668792073f091"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:48:20.730752Z","signature_b64":"9JhU7mwJ6pPWo3jBo03xGmdBdxyqdnkPizCFYxgYnPWiU3RbPeYckRssxpLkPS34huMtvkpC3l1NDsLgENgTCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32dffc489f6e26840205a1ae862631f0a6145cb69080d13980e0c62fa394d610","last_reissued_at":"2026-07-05T03:48:20.730264Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:48:20.730264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Neural Approaches to Conversational Information Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Chenyan Xiong, Jianfeng Gao, Nick Craswell, Paul Bennett","submitted_at":"2022-01-13T19:04:59Z","abstract_excerpt":"A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or written form. Recent progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. As a result, we have witnesse"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.05176","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/2201.05176/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":"2201.05176","created_at":"2026-07-05T03:48:20.730323+00:00"},{"alias_kind":"arxiv_version","alias_value":"2201.05176v1","created_at":"2026-07-05T03:48:20.730323+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.05176","created_at":"2026-07-05T03:48:20.730323+00:00"},{"alias_kind":"pith_short_12","alias_value":"GLP7YSE7NYTI","created_at":"2026-07-05T03:48:20.730323+00:00"},{"alias_kind":"pith_short_16","alias_value":"GLP7YSE7NYTIIAQF","created_at":"2026-07-05T03:48:20.730323+00:00"},{"alias_kind":"pith_short_8","alias_value":"GLP7YSE7","created_at":"2026-07-05T03:48:20.730323+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2401.03568","citing_title":"Agent AI: Surveying the Horizons of Multimodal Interaction","ref_index":65,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C","json":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C.json","graph_json":"https://pith.science/api/pith-number/GLP7YSE7NYTIIAQFUGXIMJRR6C/graph.json","events_json":"https://pith.science/api/pith-number/GLP7YSE7NYTIIAQFUGXIMJRR6C/events.json","paper":"https://pith.science/paper/GLP7YSE7"},"agent_actions":{"view_html":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C","download_json":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C.json","view_paper":"https://pith.science/paper/GLP7YSE7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2201.05176&json=true","fetch_graph":"https://pith.science/api/pith-number/GLP7YSE7NYTIIAQFUGXIMJRR6C/graph.json","fetch_events":"https://pith.science/api/pith-number/GLP7YSE7NYTIIAQFUGXIMJRR6C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C/action/storage_attestation","attest_author":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C/action/author_attestation","sign_citation":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C/action/citation_signature","submit_replication":"https://pith.science/pith/GLP7YSE7NYTIIAQFUGXIMJRR6C/action/replication_record"}},"created_at":"2026-07-05T03:48:20.730323+00:00","updated_at":"2026-07-05T03:48:20.730323+00:00"}