{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:O4USJFFESN5UNMHQGQLF7COCSS","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"dcf47d823015362bc15a96c0519cccb07e2bd78089007ae6136b10a688dde5b2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-11-17T20:31:16Z","title_canon_sha256":"76b01534bdfe0926e44b33e1bc3a24e3866b4a3fa9462bc8f0bf0b4ed8550aa1"},"schema_version":"1.0","source":{"id":"2111.09381","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.09381","created_at":"2026-07-05T03:33:10Z"},{"alias_kind":"arxiv_version","alias_value":"2111.09381v1","created_at":"2026-07-05T03:33:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.09381","created_at":"2026-07-05T03:33:10Z"},{"alias_kind":"pith_short_12","alias_value":"O4USJFFESN5U","created_at":"2026-07-05T03:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"O4USJFFESN5UNMHQ","created_at":"2026-07-05T03:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"O4USJFFE","created_at":"2026-07-05T03:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:4ed062b7eb27999db11aa6f104f54a13363acd7d91337eb33e3f0d83018b48af","target":"graph","created_at":"2026-07-05T03:33:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2111.09381/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present MEDCOD, a Medically-Accurate, Emotive, Diverse, and Controllable Dialog system with a unique approach to the natural language generator module. MEDCOD has been developed and evaluated specifically for the history taking task. It integrates the advantage of a traditional modular approach to incorporate (medical) domain knowledge with modern deep learning techniques to generate flexible, human-like natural language expressions. Two key aspects of MEDCOD's natural language output are described in detail. First, the generated sentences are emotive and empathetic, similar to how a doctor","authors_text":"Anitha Kannan, Costa Huang, Ilya Valmianski, Li Deng, Namit Katariya, Rhys Compton, Xavier Amatriain","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-11-17T20:31:16Z","title":"MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.09381","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4ddda76bd30a2ad481b44f1ada7f0a969c37528e71351961d376d984262420fe","target":"record","created_at":"2026-07-05T03:33:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"dcf47d823015362bc15a96c0519cccb07e2bd78089007ae6136b10a688dde5b2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-11-17T20:31:16Z","title_canon_sha256":"76b01534bdfe0926e44b33e1bc3a24e3866b4a3fa9462bc8f0bf0b4ed8550aa1"},"schema_version":"1.0","source":{"id":"2111.09381","kind":"arxiv","version":1}},"canonical_sha256":"77292494a4937b46b0f034165f89c294ad2537021350cbe714bd6861aa79c25b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77292494a4937b46b0f034165f89c294ad2537021350cbe714bd6861aa79c25b","first_computed_at":"2026-07-05T03:33:10.863099Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:33:10.863099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SmW5PhJGPipUDqR6MDdZ3HqNu2JrfTQSSlc0nv1CezzKprGXHml5nkp/+lXjw7waMwQsFIcDmTnVySUWY73zCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:33:10.863619Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.09381","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4ddda76bd30a2ad481b44f1ada7f0a969c37528e71351961d376d984262420fe","sha256:4ed062b7eb27999db11aa6f104f54a13363acd7d91337eb33e3f0d83018b48af"],"state_sha256":"7f8aeb2c86da47988cd32a1ecffaf301c30f71d2875ac93229d50267027b8f88"}