{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:RRLNK5Y4HGYW2BCBFOUALVOQP3","short_pith_number":"pith:RRLNK5Y4","canonical_record":{"source":{"id":"1512.04650","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-12-15T04:55:06Z","cross_cats_sorted":[],"title_canon_sha256":"6d49bbece330f6efd6b456ec582182f7e8eeaeb0333f3b3c9f684b08929001a7","abstract_canon_sha256":"02aa0ada5580ced0ebfc6e87defc34426eb41b8f353c179fb1105a6fedf1fe30"},"schema_version":"1.0"},"canonical_sha256":"8c56d5771c39b16d04412ba805d5d07ef79b44fad47023b754073abcd9c3d58f","source":{"kind":"arxiv","id":"1512.04650","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04650","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04650v2","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04650","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"pith_short_12","alias_value":"RRLNK5Y4HGYW","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_16","alias_value":"RRLNK5Y4HGYW2BCB","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_8","alias_value":"RRLNK5Y4","created_at":"2026-05-18T12:29:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:RRLNK5Y4HGYW2BCBFOUALVOQP3","target":"record","payload":{"canonical_record":{"source":{"id":"1512.04650","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-12-15T04:55:06Z","cross_cats_sorted":[],"title_canon_sha256":"6d49bbece330f6efd6b456ec582182f7e8eeaeb0333f3b3c9f684b08929001a7","abstract_canon_sha256":"02aa0ada5580ced0ebfc6e87defc34426eb41b8f353c179fb1105a6fedf1fe30"},"schema_version":"1.0"},"canonical_sha256":"8c56d5771c39b16d04412ba805d5d07ef79b44fad47023b754073abcd9c3d58f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:16:29.358224Z","signature_b64":"dvnms7kZax5wadWym9i4K8IPxxGgt3tkvREnVWy0vD2c7PnK54zQf+Aym6HSg0Q/f9EISZ/USUXq8V1jV03hCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c56d5771c39b16d04412ba805d5d07ef79b44fad47023b754073abcd9c3d58f","last_reissued_at":"2026-05-18T01:16:29.357700Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:16:29.357700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.04650","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:16:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g7QnPKRFdENYd/cWnnTxBxa+a11/w0ALZeFozQsD/sIdc1pL2EINkgQBcKoQ1dTGCyzJVVWsnzRPX2upXKYsCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T08:10:40.808557Z"},"content_sha256":"1caed8aadd428f91387501a862083bb37904d3cb70be62a195f857e50329aaa9","schema_version":"1.0","event_id":"sha256:1caed8aadd428f91387501a862083bb37904d3cb70be62a195f857e50329aaa9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:RRLNK5Y4HGYW2BCBFOUALVOQP3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hua Wu, Maosong Sun, Shiqi Shen, Wei He, Yang Liu, Yong Cheng, Zhongjun He","submitted_at":"2015-12-15T04:55:06Z","abstract_excerpt":"The attentional mechanism has proven to be effective in improving end-to-end neural machine translation. However, due to the intricate structural divergence between natural languages, unidirectional attention-based models might only capture partial aspects of attentional regularities. We propose agreement-based joint training for bidirectional attention-based end-to-end neural machine translation. Instead of training source-to-target and target-to-source translation models independently,our approach encourages the two complementary models to agree on word alignment matrices on the same trainin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04650","kind":"arxiv","version":2},"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":"2026-05-18T01:16:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XK8Mf03x67cDepiPTBD/oYpMhGmbYOxrpODtQTtLkuaCI6biRev1afuYp8Ul9dtYvfoRuXhmb5ffsvHQh2ltAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T08:10:40.809252Z"},"content_sha256":"f76ab8b9adc1c1af53819e865f5d146369da905adad6aa51c569ccf199499f7b","schema_version":"1.0","event_id":"sha256:f76ab8b9adc1c1af53819e865f5d146369da905adad6aa51c569ccf199499f7b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/bundle.json","state_url":"https://pith.science/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/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":"2026-06-03T08:10:40Z","links":{"resolver":"https://pith.science/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3","bundle":"https://pith.science/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/bundle.json","state":"https://pith.science/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RRLNK5Y4HGYW2BCBFOUALVOQP3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:RRLNK5Y4HGYW2BCBFOUALVOQP3","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":"02aa0ada5580ced0ebfc6e87defc34426eb41b8f353c179fb1105a6fedf1fe30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-12-15T04:55:06Z","title_canon_sha256":"6d49bbece330f6efd6b456ec582182f7e8eeaeb0333f3b3c9f684b08929001a7"},"schema_version":"1.0","source":{"id":"1512.04650","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04650","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04650v2","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04650","created_at":"2026-05-18T01:16:29Z"},{"alias_kind":"pith_short_12","alias_value":"RRLNK5Y4HGYW","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_16","alias_value":"RRLNK5Y4HGYW2BCB","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_8","alias_value":"RRLNK5Y4","created_at":"2026-05-18T12:29:39Z"}],"graph_snapshots":[{"event_id":"sha256:f76ab8b9adc1c1af53819e865f5d146369da905adad6aa51c569ccf199499f7b","target":"graph","created_at":"2026-05-18T01:16:29Z","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":"The attentional mechanism has proven to be effective in improving end-to-end neural machine translation. However, due to the intricate structural divergence between natural languages, unidirectional attention-based models might only capture partial aspects of attentional regularities. We propose agreement-based joint training for bidirectional attention-based end-to-end neural machine translation. Instead of training source-to-target and target-to-source translation models independently,our approach encourages the two complementary models to agree on word alignment matrices on the same trainin","authors_text":"Hua Wu, Maosong Sun, Shiqi Shen, Wei He, Yang Liu, Yong Cheng, Zhongjun He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-12-15T04:55:06Z","title":"Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04650","kind":"arxiv","version":2},"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":"sha256:1caed8aadd428f91387501a862083bb37904d3cb70be62a195f857e50329aaa9","target":"record","created_at":"2026-05-18T01:16:29Z","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":"02aa0ada5580ced0ebfc6e87defc34426eb41b8f353c179fb1105a6fedf1fe30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-12-15T04:55:06Z","title_canon_sha256":"6d49bbece330f6efd6b456ec582182f7e8eeaeb0333f3b3c9f684b08929001a7"},"schema_version":"1.0","source":{"id":"1512.04650","kind":"arxiv","version":2}},"canonical_sha256":"8c56d5771c39b16d04412ba805d5d07ef79b44fad47023b754073abcd9c3d58f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c56d5771c39b16d04412ba805d5d07ef79b44fad47023b754073abcd9c3d58f","first_computed_at":"2026-05-18T01:16:29.357700Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:16:29.357700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dvnms7kZax5wadWym9i4K8IPxxGgt3tkvREnVWy0vD2c7PnK54zQf+Aym6HSg0Q/f9EISZ/USUXq8V1jV03hCg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:16:29.358224Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.04650","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1caed8aadd428f91387501a862083bb37904d3cb70be62a195f857e50329aaa9","sha256:f76ab8b9adc1c1af53819e865f5d146369da905adad6aa51c569ccf199499f7b"],"state_sha256":"3de0ed374892a3ed898489d2460d1eaf7c0f6e34b40123e176822cfb397d9c09"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PcIN6kmBSq8CQex4RE99va4/GDi3wI0UP4nj6HuSg0n/L8dsmL6SZBI9n/m5KSo2tqPkbFJr5yPsdu14ww68Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T08:10:40.812616Z","bundle_sha256":"a5902bdea9962a7a280df13e8790b90d11efc4725572aa4535fa7e80b9a0e47f"}}