{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CASM674YSV4CJOKQBN2ZSU5BLO","short_pith_number":"pith:CASM674Y","canonical_record":{"source":{"id":"1808.10267","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-08-30T13:18:57Z","cross_cats_sorted":[],"title_canon_sha256":"66bec4bdf18f198aaaf6154cfeba5804304402804de9a052fbea829df286719a","abstract_canon_sha256":"b8cdf1bbde858721c0556ca22f602827bf2ae80deb5c015ceb8821341f131097"},"schema_version":"1.0"},"canonical_sha256":"1024cf7f98957824b9500b759953a15b874246b58656efa8ded436e6c0fecea7","source":{"kind":"arxiv","id":"1808.10267","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.10267","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"arxiv_version","alias_value":"1808.10267v1","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.10267","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"pith_short_12","alias_value":"CASM674YSV4C","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CASM674YSV4CJOKQ","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CASM674Y","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CASM674YSV4CJOKQBN2ZSU5BLO","target":"record","payload":{"canonical_record":{"source":{"id":"1808.10267","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-08-30T13:18:57Z","cross_cats_sorted":[],"title_canon_sha256":"66bec4bdf18f198aaaf6154cfeba5804304402804de9a052fbea829df286719a","abstract_canon_sha256":"b8cdf1bbde858721c0556ca22f602827bf2ae80deb5c015ceb8821341f131097"},"schema_version":"1.0"},"canonical_sha256":"1024cf7f98957824b9500b759953a15b874246b58656efa8ded436e6c0fecea7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:49.281078Z","signature_b64":"LthXbTAFZb74R0bKhslxGrZtUGgxAQ+1W5XaUgUVLMO/k0kY7vTH021xwEAihYtri6IsokH7YIJmiKnnTBwaBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1024cf7f98957824b9500b759953a15b874246b58656efa8ded436e6c0fecea7","last_reissued_at":"2026-05-18T00:06:49.280607Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:49.280607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.10267","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:06:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ldxMTe/8V7wwbANgo5gayZ5lc19OUVwYYb/Reslv6rjWekO0PsjBehSARZtspjxdMlR26GwrL5z66hb7BvXPBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T12:47:11.702191Z"},"content_sha256":"f45b0ebe99cd0bcbbb1ac211c38be9ac780d9ebbadcc30257d2428cd0b0a5f8c","schema_version":"1.0","event_id":"sha256:f45b0ebe99cd0bcbbb1ac211c38be9ac780d9ebbadcc30257d2428cd0b0a5f8c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CASM674YSV4CJOKQBN2ZSU5BLO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Source Syntactic Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Anna Currey, Kenneth Heafield","submitted_at":"2018-08-30T13:18:57Z","abstract_excerpt":"We introduce a novel multi-source technique for incorporating source syntax into neural machine translation using linearized parses. This is achieved by employing separate encoders for the sequential and parsed versions of the same source sentence; the resulting representations are then combined using a hierarchical attention mechanism. The proposed model improves over both seq2seq and parsed baselines by over 1 BLEU on the WMT17 English-German task. Further analysis shows that our multi-source syntactic model is able to translate successfully without any parsed input, unlike standard parsed m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.10267","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:06:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EFXI+/ke8k01iwgJECoozQ0hjnLNvbA/O1xcMaeg39mP+dU30MWxBtMc/VEVKoTjfhaAnSq+L7+MsmenxtCYBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T12:47:11.702550Z"},"content_sha256":"6809e719e4cdce9f04650811e3632002661d17933bbfaa2ce8712c82c25e7c1f","schema_version":"1.0","event_id":"sha256:6809e719e4cdce9f04650811e3632002661d17933bbfaa2ce8712c82c25e7c1f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CASM674YSV4CJOKQBN2ZSU5BLO/bundle.json","state_url":"https://pith.science/pith/CASM674YSV4CJOKQBN2ZSU5BLO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CASM674YSV4CJOKQBN2ZSU5BLO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-03T12:47:11Z","links":{"resolver":"https://pith.science/pith/CASM674YSV4CJOKQBN2ZSU5BLO","bundle":"https://pith.science/pith/CASM674YSV4CJOKQBN2ZSU5BLO/bundle.json","state":"https://pith.science/pith/CASM674YSV4CJOKQBN2ZSU5BLO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CASM674YSV4CJOKQBN2ZSU5BLO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CASM674YSV4CJOKQBN2ZSU5BLO","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":"b8cdf1bbde858721c0556ca22f602827bf2ae80deb5c015ceb8821341f131097","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-08-30T13:18:57Z","title_canon_sha256":"66bec4bdf18f198aaaf6154cfeba5804304402804de9a052fbea829df286719a"},"schema_version":"1.0","source":{"id":"1808.10267","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.10267","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"arxiv_version","alias_value":"1808.10267v1","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.10267","created_at":"2026-05-18T00:06:49Z"},{"alias_kind":"pith_short_12","alias_value":"CASM674YSV4C","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CASM674YSV4CJOKQ","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CASM674Y","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:6809e719e4cdce9f04650811e3632002661d17933bbfaa2ce8712c82c25e7c1f","target":"graph","created_at":"2026-05-18T00:06:49Z","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"},"paper":{"abstract_excerpt":"We introduce a novel multi-source technique for incorporating source syntax into neural machine translation using linearized parses. This is achieved by employing separate encoders for the sequential and parsed versions of the same source sentence; the resulting representations are then combined using a hierarchical attention mechanism. The proposed model improves over both seq2seq and parsed baselines by over 1 BLEU on the WMT17 English-German task. Further analysis shows that our multi-source syntactic model is able to translate successfully without any parsed input, unlike standard parsed m","authors_text":"Anna Currey, Kenneth Heafield","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-08-30T13:18:57Z","title":"Multi-Source Syntactic Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.10267","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:f45b0ebe99cd0bcbbb1ac211c38be9ac780d9ebbadcc30257d2428cd0b0a5f8c","target":"record","created_at":"2026-05-18T00:06:49Z","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":"b8cdf1bbde858721c0556ca22f602827bf2ae80deb5c015ceb8821341f131097","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-08-30T13:18:57Z","title_canon_sha256":"66bec4bdf18f198aaaf6154cfeba5804304402804de9a052fbea829df286719a"},"schema_version":"1.0","source":{"id":"1808.10267","kind":"arxiv","version":1}},"canonical_sha256":"1024cf7f98957824b9500b759953a15b874246b58656efa8ded436e6c0fecea7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1024cf7f98957824b9500b759953a15b874246b58656efa8ded436e6c0fecea7","first_computed_at":"2026-05-18T00:06:49.280607Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:06:49.280607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LthXbTAFZb74R0bKhslxGrZtUGgxAQ+1W5XaUgUVLMO/k0kY7vTH021xwEAihYtri6IsokH7YIJmiKnnTBwaBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:06:49.281078Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.10267","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f45b0ebe99cd0bcbbb1ac211c38be9ac780d9ebbadcc30257d2428cd0b0a5f8c","sha256:6809e719e4cdce9f04650811e3632002661d17933bbfaa2ce8712c82c25e7c1f"],"state_sha256":"7d874d7f3bb0fc36de4b936c7e78475d2b0f18af2ca24c13a5c83c2b3174b670"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yjc5o74ccC4u90wc6Pdi5HX35zPedrezLEwkIzVeCMkbE02HvG7UI4Er92PGVs72hq8aYQvhU068W9RKJJ7nDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T12:47:11.704567Z","bundle_sha256":"502746eb8cdc2e1e9f360691adabd04640f08d0354ce1b60f84b6ac4f4b57580"}}