{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:HR5L6VCNLHPJHNOBPGXGGVPE2F","short_pith_number":"pith:HR5L6VCN","schema_version":"1.0","canonical_sha256":"3c7abf544d59de93b5c179ae6355e4d1534ae047fc425279b82fc290084b6a1d","source":{"kind":"arxiv","id":"1909.00531","version":1},"attestation_state":"computed","paper":{"title":"Improving Context-aware Neural Machine Translation with Target-side Context","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hayahide Yamagishi, Mamoru Komachi","submitted_at":"2019-09-02T04:04:18Z","abstract_excerpt":"In recent years, several studies on neural machine translation (NMT) have attempted to use document-level context by using a multi-encoder and two attention mechanisms to read the current and previous sentences to incorporate the context of the previous sentences. These studies concluded that the target-side context is less useful than the source-side context. However, we considered that the reason why the target-side context is less useful lies in the architecture used to model these contexts.\n  Therefore, in this study, we investigate how the target-side context can improve context-aware neu"},"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":"1909.00531","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-09-02T04:04:18Z","cross_cats_sorted":[],"title_canon_sha256":"340ddf0b312d6df408545c1629f56627632b4a668de03b08f44c6c4c5ab4380f","abstract_canon_sha256":"80495512f394668526e1a715a7a2f86ebd6c3b5ec52cc2b4d42b70f6f22bebda"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:01:10.557726Z","signature_b64":"8JB0Li7Ttb6uOeBfprOq3TvAHTYeCV6iYzVTzZ4aDsqvUOupDwRW7YCAJ2InjxUn06D8GF59pusD/IJUd1kGCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c7abf544d59de93b5c179ae6355e4d1534ae047fc425279b82fc290084b6a1d","last_reissued_at":"2026-07-05T00:01:10.557248Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:01:10.557248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improving Context-aware Neural Machine Translation with Target-side Context","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hayahide Yamagishi, Mamoru Komachi","submitted_at":"2019-09-02T04:04:18Z","abstract_excerpt":"In recent years, several studies on neural machine translation (NMT) have attempted to use document-level context by using a multi-encoder and two attention mechanisms to read the current and previous sentences to incorporate the context of the previous sentences. These studies concluded that the target-side context is less useful than the source-side context. However, we considered that the reason why the target-side context is less useful lies in the architecture used to model these contexts.\n  Therefore, in this study, we investigate how the target-side context can improve context-aware neu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.00531","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/1909.00531/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":"1909.00531","created_at":"2026-07-05T00:01:10.557304+00:00"},{"alias_kind":"arxiv_version","alias_value":"1909.00531v1","created_at":"2026-07-05T00:01:10.557304+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.00531","created_at":"2026-07-05T00:01:10.557304+00:00"},{"alias_kind":"pith_short_12","alias_value":"HR5L6VCNLHPJ","created_at":"2026-07-05T00:01:10.557304+00:00"},{"alias_kind":"pith_short_16","alias_value":"HR5L6VCNLHPJHNOB","created_at":"2026-07-05T00:01:10.557304+00:00"},{"alias_kind":"pith_short_8","alias_value":"HR5L6VCN","created_at":"2026-07-05T00:01:10.557304+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/HR5L6VCNLHPJHNOBPGXGGVPE2F","json":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F.json","graph_json":"https://pith.science/api/pith-number/HR5L6VCNLHPJHNOBPGXGGVPE2F/graph.json","events_json":"https://pith.science/api/pith-number/HR5L6VCNLHPJHNOBPGXGGVPE2F/events.json","paper":"https://pith.science/paper/HR5L6VCN"},"agent_actions":{"view_html":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F","download_json":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F.json","view_paper":"https://pith.science/paper/HR5L6VCN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1909.00531&json=true","fetch_graph":"https://pith.science/api/pith-number/HR5L6VCNLHPJHNOBPGXGGVPE2F/graph.json","fetch_events":"https://pith.science/api/pith-number/HR5L6VCNLHPJHNOBPGXGGVPE2F/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F/action/storage_attestation","attest_author":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F/action/author_attestation","sign_citation":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F/action/citation_signature","submit_replication":"https://pith.science/pith/HR5L6VCNLHPJHNOBPGXGGVPE2F/action/replication_record"}},"created_at":"2026-07-05T00:01:10.557304+00:00","updated_at":"2026-07-05T00:01:10.557304+00:00"}