{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:VAEIAAHADMFYQ3B7CKRONCZ2S2","short_pith_number":"pith:VAEIAAHA","schema_version":"1.0","canonical_sha256":"a8088000e01b0b886c3f12a2e68b3a96ad0015e4d2c0b2d5049a556bb992363c","source":{"kind":"arxiv","id":"1811.00681","version":2},"attestation_state":"computed","paper":{"title":"On the Generation of Medical Question-Answer Pairs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Kai Wang, Nan Du, Shen Ge, Sheng Shen, Tao Yang, Wei Fan, Xian Wu, Xingzheng Liang, Yaliang Li, Yusheng Xie","submitted_at":"2018-11-01T23:50:43Z","abstract_excerpt":"Question answering (QA) has achieved promising progress recently. However, answering a question in real-world scenarios like the medical domain is still challenging, due to the requirement of external knowledge and the insufficient quantity of high-quality training data. In the light of these challenges, we study the task of generating medical QA pairs in this paper. With the insight that each medical question can be considered as a sample from the latent distribution of questions given answers, we propose an automated medical QA pair generation framework, consisting of an unsupervised key phr"},"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":"1811.00681","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-11-01T23:50:43Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"7426144430b3bc3ed51b51c87bc9e7616df5fd1df6ba85286fa42fc40f2ef3e6","abstract_canon_sha256":"5210b3ef4db59399bf26a9b9f824fbeccb3eeb9bbc1b7a99e5442e8133db77bb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:24:35.992807Z","signature_b64":"aGwS4jqwwn8UKSPULUjxixyscgOlFCezDtuiMjtHL0MeomgSfH0D1ijQ9brD6yyHkb+NzpnmjSHpwrwVtYHkDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a8088000e01b0b886c3f12a2e68b3a96ad0015e4d2c0b2d5049a556bb992363c","last_reissued_at":"2026-07-05T00:24:35.992355Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:24:35.992355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the Generation of Medical Question-Answer Pairs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Kai Wang, Nan Du, Shen Ge, Sheng Shen, Tao Yang, Wei Fan, Xian Wu, Xingzheng Liang, Yaliang Li, Yusheng Xie","submitted_at":"2018-11-01T23:50:43Z","abstract_excerpt":"Question answering (QA) has achieved promising progress recently. However, answering a question in real-world scenarios like the medical domain is still challenging, due to the requirement of external knowledge and the insufficient quantity of high-quality training data. In the light of these challenges, we study the task of generating medical QA pairs in this paper. With the insight that each medical question can be considered as a sample from the latent distribution of questions given answers, we propose an automated medical QA pair generation framework, consisting of an unsupervised key phr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.00681","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/1811.00681/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":"1811.00681","created_at":"2026-07-05T00:24:35.992419+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.00681v2","created_at":"2026-07-05T00:24:35.992419+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.00681","created_at":"2026-07-05T00:24:35.992419+00:00"},{"alias_kind":"pith_short_12","alias_value":"VAEIAAHADMFY","created_at":"2026-07-05T00:24:35.992419+00:00"},{"alias_kind":"pith_short_16","alias_value":"VAEIAAHADMFYQ3B7","created_at":"2026-07-05T00:24:35.992419+00:00"},{"alias_kind":"pith_short_8","alias_value":"VAEIAAHA","created_at":"2026-07-05T00:24:35.992419+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/VAEIAAHADMFYQ3B7CKRONCZ2S2","json":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2.json","graph_json":"https://pith.science/api/pith-number/VAEIAAHADMFYQ3B7CKRONCZ2S2/graph.json","events_json":"https://pith.science/api/pith-number/VAEIAAHADMFYQ3B7CKRONCZ2S2/events.json","paper":"https://pith.science/paper/VAEIAAHA"},"agent_actions":{"view_html":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2","download_json":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2.json","view_paper":"https://pith.science/paper/VAEIAAHA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.00681&json=true","fetch_graph":"https://pith.science/api/pith-number/VAEIAAHADMFYQ3B7CKRONCZ2S2/graph.json","fetch_events":"https://pith.science/api/pith-number/VAEIAAHADMFYQ3B7CKRONCZ2S2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2/action/storage_attestation","attest_author":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2/action/author_attestation","sign_citation":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2/action/citation_signature","submit_replication":"https://pith.science/pith/VAEIAAHADMFYQ3B7CKRONCZ2S2/action/replication_record"}},"created_at":"2026-07-05T00:24:35.992419+00:00","updated_at":"2026-07-05T00:24:35.992419+00:00"}