{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:C6XAIGHD63WIRKES3B4G2DWYDT","short_pith_number":"pith:C6XAIGHD","schema_version":"1.0","canonical_sha256":"17ae0418e3f6ec88a892d8786d0ed81cd4215a10bba33214151b38099a201e09","source":{"kind":"arxiv","id":"2405.05513","version":1},"attestation_state":"computed","paper":{"title":"Automatic question generation for propositional logical equivalences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM"],"primary_cat":"cs.CL","authors_text":"Haoming Yu, Xinyu Wang, Yicheng Yang, Zhiyuan Li","submitted_at":"2024-05-09T02:44:42Z","abstract_excerpt":"The increase in academic dishonesty cases among college students has raised concern, particularly due to the shift towards online learning caused by the pandemic. We aim to develop and implement a method capable of generating tailored questions for each student. The use of Automatic Question Generation (AQG) is a possible solution. Previous studies have investigated AQG frameworks in education, which include validity, user-defined difficulty, and personalized problem generation. Our new AQG approach produces logical equivalence problems for Discrete Mathematics, which is a core course for year"},"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":"2405.05513","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-09T02:44:42Z","cross_cats_sorted":["cs.DM"],"title_canon_sha256":"ddf02181e8db85130e32f0f2f87579ea25d74e6db2561594fc940b5e68a33c20","abstract_canon_sha256":"1e0e54e83edc2cff62d84dfeb63e741eaf32339428d07950f055d8b630486a8f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:17:19.212003Z","signature_b64":"U4O0HB3UdLu3DoWTeWINZ5EoziSDB4aub8QJpWgTJdX/5AlSeCaZ6o2KBDBzeezewnaukSj3HYtnAmniyyFfAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17ae0418e3f6ec88a892d8786d0ed81cd4215a10bba33214151b38099a201e09","last_reissued_at":"2026-07-05T08:17:19.211551Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:17:19.211551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automatic question generation for propositional logical equivalences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM"],"primary_cat":"cs.CL","authors_text":"Haoming Yu, Xinyu Wang, Yicheng Yang, Zhiyuan Li","submitted_at":"2024-05-09T02:44:42Z","abstract_excerpt":"The increase in academic dishonesty cases among college students has raised concern, particularly due to the shift towards online learning caused by the pandemic. We aim to develop and implement a method capable of generating tailored questions for each student. The use of Automatic Question Generation (AQG) is a possible solution. Previous studies have investigated AQG frameworks in education, which include validity, user-defined difficulty, and personalized problem generation. Our new AQG approach produces logical equivalence problems for Discrete Mathematics, which is a core course for year"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.05513","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/2405.05513/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":"2405.05513","created_at":"2026-07-05T08:17:19.211605+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.05513v1","created_at":"2026-07-05T08:17:19.211605+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.05513","created_at":"2026-07-05T08:17:19.211605+00:00"},{"alias_kind":"pith_short_12","alias_value":"C6XAIGHD63WI","created_at":"2026-07-05T08:17:19.211605+00:00"},{"alias_kind":"pith_short_16","alias_value":"C6XAIGHD63WIRKES","created_at":"2026-07-05T08:17:19.211605+00:00"},{"alias_kind":"pith_short_8","alias_value":"C6XAIGHD","created_at":"2026-07-05T08:17:19.211605+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/C6XAIGHD63WIRKES3B4G2DWYDT","json":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT.json","graph_json":"https://pith.science/api/pith-number/C6XAIGHD63WIRKES3B4G2DWYDT/graph.json","events_json":"https://pith.science/api/pith-number/C6XAIGHD63WIRKES3B4G2DWYDT/events.json","paper":"https://pith.science/paper/C6XAIGHD"},"agent_actions":{"view_html":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT","download_json":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT.json","view_paper":"https://pith.science/paper/C6XAIGHD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.05513&json=true","fetch_graph":"https://pith.science/api/pith-number/C6XAIGHD63WIRKES3B4G2DWYDT/graph.json","fetch_events":"https://pith.science/api/pith-number/C6XAIGHD63WIRKES3B4G2DWYDT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT/action/storage_attestation","attest_author":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT/action/author_attestation","sign_citation":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT/action/citation_signature","submit_replication":"https://pith.science/pith/C6XAIGHD63WIRKES3B4G2DWYDT/action/replication_record"}},"created_at":"2026-07-05T08:17:19.211605+00:00","updated_at":"2026-07-05T08:17:19.211605+00:00"}