{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:WC23TFNRKSQCQ6FIMNP3WJGPSI","short_pith_number":"pith:WC23TFNR","schema_version":"1.0","canonical_sha256":"b0b5b995b154a02878a8635fbb24cf92395ef6f045aad46c1d18929a4c03be70","source":{"kind":"arxiv","id":"1711.05568","version":1},"attestation_state":"computed","paper":{"title":"Dialogue Act Recognition via CRF-Attentive Structured Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Deng Cai, Rongqin Yang, Xiaofei He, Zheqian Chen, Zhou Zhao","submitted_at":"2017-11-15T13:43:02Z","abstract_excerpt":"Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention. Currently, many existing approaches formulate the DAR problem ranging from multi-classification to structured prediction, which suffer from handcrafted feature extensions and attentive contextual structural dependencies. In this paper, we consider the problem of DAR from the viewpoint of extending richer Conditional Random Field (CRF) structural dependencies without abandoning end-to-end training. We incorporate hierarc"},"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":"1711.05568","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-11-15T13:43:02Z","cross_cats_sorted":[],"title_canon_sha256":"f4d3ad2c06fe25b8bd4c44daf60d43694735fbd3f79a75d4217bb962b6d02383","abstract_canon_sha256":"ec8e740a7a40edd66b6047561a78bd93683e2bee86bda8a7a6e9f74c6a60a6df"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:29.505065Z","signature_b64":"1WY06FfI74gLxeTjdbCgAbDVZ1s79+cz/ShU4FldcJXqNfFjf1ehSnNDxAJV0mvajbETsmtJE+123g0qvwULDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0b5b995b154a02878a8635fbb24cf92395ef6f045aad46c1d18929a4c03be70","last_reissued_at":"2026-05-18T00:30:29.504527Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:29.504527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dialogue Act Recognition via CRF-Attentive Structured Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Deng Cai, Rongqin Yang, Xiaofei He, Zheqian Chen, Zhou Zhao","submitted_at":"2017-11-15T13:43:02Z","abstract_excerpt":"Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention. Currently, many existing approaches formulate the DAR problem ranging from multi-classification to structured prediction, which suffer from handcrafted feature extensions and attentive contextual structural dependencies. In this paper, we consider the problem of DAR from the viewpoint of extending richer Conditional Random Field (CRF) structural dependencies without abandoning end-to-end training. We incorporate hierarc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.05568","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":""},"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":"1711.05568","created_at":"2026-05-18T00:30:29.504611+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.05568v1","created_at":"2026-05-18T00:30:29.504611+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.05568","created_at":"2026-05-18T00:30:29.504611+00:00"},{"alias_kind":"pith_short_12","alias_value":"WC23TFNRKSQC","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_16","alias_value":"WC23TFNRKSQCQ6FI","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_8","alias_value":"WC23TFNR","created_at":"2026-05-18T12:31:53.515858+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/WC23TFNRKSQCQ6FIMNP3WJGPSI","json":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI.json","graph_json":"https://pith.science/api/pith-number/WC23TFNRKSQCQ6FIMNP3WJGPSI/graph.json","events_json":"https://pith.science/api/pith-number/WC23TFNRKSQCQ6FIMNP3WJGPSI/events.json","paper":"https://pith.science/paper/WC23TFNR"},"agent_actions":{"view_html":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI","download_json":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI.json","view_paper":"https://pith.science/paper/WC23TFNR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.05568&json=true","fetch_graph":"https://pith.science/api/pith-number/WC23TFNRKSQCQ6FIMNP3WJGPSI/graph.json","fetch_events":"https://pith.science/api/pith-number/WC23TFNRKSQCQ6FIMNP3WJGPSI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI/action/storage_attestation","attest_author":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI/action/author_attestation","sign_citation":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI/action/citation_signature","submit_replication":"https://pith.science/pith/WC23TFNRKSQCQ6FIMNP3WJGPSI/action/replication_record"}},"created_at":"2026-05-18T00:30:29.504611+00:00","updated_at":"2026-05-18T00:30:29.504611+00:00"}