{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:XDO7UZ45UNI364WXNDKIOVQFEO","short_pith_number":"pith:XDO7UZ45","schema_version":"1.0","canonical_sha256":"b8ddfa679da351bf72d768d4875605238ed390cef6b88c3771b8fda9c9f1f53c","source":{"kind":"arxiv","id":"1909.02273","version":1},"attestation_state":"computed","paper":{"title":"Source Dependency-Aware Transformer with Supervised Self-Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chengyi Wang, Shuangzhi Wu, Shujie Liu","submitted_at":"2019-09-05T09:17:37Z","abstract_excerpt":"Recently, Transformer has achieved the state-of-the-art performance on many machine translation tasks. However, without syntax knowledge explicitly considered in the encoder, incorrect context information that violates the syntax structure may be integrated into source hidden states, leading to erroneous translations. In this paper, we propose a novel method to incorporate source dependencies into the Transformer. Specifically, we adopt the source dependency tree and define two matrices to represent the dependency relations. Based on the matrices, two heads in the multi-head self-attention mod"},"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":"1909.02273","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-09-05T09:17:37Z","cross_cats_sorted":[],"title_canon_sha256":"dcacfbf876a4e67febe85937d80296a3ff677bb56b9835413bec72cfeb2817f1","abstract_canon_sha256":"f4ff706a83d4372162ba9704fc1a47714eb9576d91ea690cbc0d3895b46a621a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:02:32.423637Z","signature_b64":"u1z/fk2P6U2ML/esPRlAHTEvDfIgQ7txHxmQTWmtrrufETco2lBbSDQ4c24dJMb+5xCybdHNLgrzsFHEgrRoCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8ddfa679da351bf72d768d4875605238ed390cef6b88c3771b8fda9c9f1f53c","last_reissued_at":"2026-07-05T00:02:32.423128Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:02:32.423128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Source Dependency-Aware Transformer with Supervised Self-Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chengyi Wang, Shuangzhi Wu, Shujie Liu","submitted_at":"2019-09-05T09:17:37Z","abstract_excerpt":"Recently, Transformer has achieved the state-of-the-art performance on many machine translation tasks. However, without syntax knowledge explicitly considered in the encoder, incorrect context information that violates the syntax structure may be integrated into source hidden states, leading to erroneous translations. In this paper, we propose a novel method to incorporate source dependencies into the Transformer. Specifically, we adopt the source dependency tree and define two matrices to represent the dependency relations. Based on the matrices, two heads in the multi-head self-attention mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.02273","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/1909.02273/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":"1909.02273","created_at":"2026-07-05T00:02:32.423198+00:00"},{"alias_kind":"arxiv_version","alias_value":"1909.02273v1","created_at":"2026-07-05T00:02:32.423198+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.02273","created_at":"2026-07-05T00:02:32.423198+00:00"},{"alias_kind":"pith_short_12","alias_value":"XDO7UZ45UNI3","created_at":"2026-07-05T00:02:32.423198+00:00"},{"alias_kind":"pith_short_16","alias_value":"XDO7UZ45UNI364WX","created_at":"2026-07-05T00:02:32.423198+00:00"},{"alias_kind":"pith_short_8","alias_value":"XDO7UZ45","created_at":"2026-07-05T00:02:32.423198+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/XDO7UZ45UNI364WXNDKIOVQFEO","json":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO.json","graph_json":"https://pith.science/api/pith-number/XDO7UZ45UNI364WXNDKIOVQFEO/graph.json","events_json":"https://pith.science/api/pith-number/XDO7UZ45UNI364WXNDKIOVQFEO/events.json","paper":"https://pith.science/paper/XDO7UZ45"},"agent_actions":{"view_html":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO","download_json":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO.json","view_paper":"https://pith.science/paper/XDO7UZ45","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1909.02273&json=true","fetch_graph":"https://pith.science/api/pith-number/XDO7UZ45UNI364WXNDKIOVQFEO/graph.json","fetch_events":"https://pith.science/api/pith-number/XDO7UZ45UNI364WXNDKIOVQFEO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO/action/storage_attestation","attest_author":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO/action/author_attestation","sign_citation":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO/action/citation_signature","submit_replication":"https://pith.science/pith/XDO7UZ45UNI364WXNDKIOVQFEO/action/replication_record"}},"created_at":"2026-07-05T00:02:32.423198+00:00","updated_at":"2026-07-05T00:02:32.423198+00:00"}