{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:H4JLFYCNG6IPBPIKGW244VGJXB","short_pith_number":"pith:H4JLFYCN","canonical_record":{"source":{"id":"1810.10181","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-24T04:08:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dbb5fa0bcd106e51f893d1c67d92381cc46ad26c365d7fe92bd7414b6a466222","abstract_canon_sha256":"8035f749866e2fce4c9d650799ace273917af4e7e96eba0c7a451e5d5e696025"},"schema_version":"1.0"},"canonical_sha256":"3f12b2e04d3790f0bd0a35b5ce54c9b84d300bd842ab7deff32b63b27c5227ad","source":{"kind":"arxiv","id":"1810.10181","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.10181","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"1810.10181v1","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.10181","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"H4JLFYCNG6IP","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"H4JLFYCNG6IPBPIK","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"H4JLFYCN","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:H4JLFYCNG6IPBPIKGW244VGJXB","target":"record","payload":{"canonical_record":{"source":{"id":"1810.10181","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-24T04:08:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dbb5fa0bcd106e51f893d1c67d92381cc46ad26c365d7fe92bd7414b6a466222","abstract_canon_sha256":"8035f749866e2fce4c9d650799ace273917af4e7e96eba0c7a451e5d5e696025"},"schema_version":"1.0"},"canonical_sha256":"3f12b2e04d3790f0bd0a35b5ce54c9b84d300bd842ab7deff32b63b27c5227ad","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:24.001914Z","signature_b64":"BsvSOblzI/UY0xgh1OZuIBKvYJYG/Y3vHmmhZfoCzKh+vZwXn54WV9SW/L0Q9ZW1jmy7VY4dvpD/sJFm924bBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3f12b2e04d3790f0bd0a35b5ce54c9b84d300bd842ab7deff32b63b27c5227ad","last_reissued_at":"2026-05-18T00:02:24.001266Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:24.001266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.10181","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":"2026-05-18T00:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BqnREDnJhwQb3lG8tqutLwRT4G6GC+fCg/G/99xp5+kYlqyNJIJiukUNo7fmyYwybHjt6y76fl2eAY5AoCLgAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:02:13.555833Z"},"content_sha256":"a181ecca9f0f9aa329b503223c5a4f5b1d4255a2855d3089b0a4e7bbbf9e0beb","schema_version":"1.0","event_id":"sha256:a181ecca9f0f9aa329b503223c5a4f5b1d4255a2855d3089b0a4e7bbbf9e0beb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:H4JLFYCNG6IPBPIKGW244VGJXB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploiting Deep Representations for Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Shuming Shi, Tong Zhang, Xing Wang, Zhaopeng Tu, Zi-Yi Dou","submitted_at":"2018-10-24T04:08:22Z","abstract_excerpt":"Advanced neural machine translation (NMT) models generally implement encoder and decoder as multiple layers, which allows systems to model complex functions and capture complicated linguistic structures. However, only the top layers of encoder and decoder are leveraged in the subsequent process, which misses the opportunity to exploit the useful information embedded in other layers. In this work, we propose to simultaneously expose all of these signals with layer aggregation and multi-layer attention mechanisms. In addition, we introduce an auxiliary regularization term to encourage different "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.10181","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":"2026-05-18T00:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wWkIF8F8I+5gwN9MQK0NhTjXM94+nOdb5Ow5wBUw+2ODgfpYFU7BHuXK9ffxXCV1tUqXubpxF94Tr1NklnbJAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:02:13.556211Z"},"content_sha256":"5634d1da14a873987100e6c2d7c44507e3c35dc0686b7d38307564fdae1b2c41","schema_version":"1.0","event_id":"sha256:5634d1da14a873987100e6c2d7c44507e3c35dc0686b7d38307564fdae1b2c41"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H4JLFYCNG6IPBPIKGW244VGJXB/bundle.json","state_url":"https://pith.science/pith/H4JLFYCNG6IPBPIKGW244VGJXB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H4JLFYCNG6IPBPIKGW244VGJXB/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":"2026-05-26T18:02:13Z","links":{"resolver":"https://pith.science/pith/H4JLFYCNG6IPBPIKGW244VGJXB","bundle":"https://pith.science/pith/H4JLFYCNG6IPBPIKGW244VGJXB/bundle.json","state":"https://pith.science/pith/H4JLFYCNG6IPBPIKGW244VGJXB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H4JLFYCNG6IPBPIKGW244VGJXB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:H4JLFYCNG6IPBPIKGW244VGJXB","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":"8035f749866e2fce4c9d650799ace273917af4e7e96eba0c7a451e5d5e696025","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-24T04:08:22Z","title_canon_sha256":"dbb5fa0bcd106e51f893d1c67d92381cc46ad26c365d7fe92bd7414b6a466222"},"schema_version":"1.0","source":{"id":"1810.10181","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.10181","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"1810.10181v1","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.10181","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"H4JLFYCNG6IP","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"H4JLFYCNG6IPBPIK","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"H4JLFYCN","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:5634d1da14a873987100e6c2d7c44507e3c35dc0686b7d38307564fdae1b2c41","target":"graph","created_at":"2026-05-18T00:02:24Z","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":"Advanced neural machine translation (NMT) models generally implement encoder and decoder as multiple layers, which allows systems to model complex functions and capture complicated linguistic structures. However, only the top layers of encoder and decoder are leveraged in the subsequent process, which misses the opportunity to exploit the useful information embedded in other layers. In this work, we propose to simultaneously expose all of these signals with layer aggregation and multi-layer attention mechanisms. In addition, we introduce an auxiliary regularization term to encourage different ","authors_text":"Shuming Shi, Tong Zhang, Xing Wang, Zhaopeng Tu, Zi-Yi Dou","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-24T04:08:22Z","title":"Exploiting Deep Representations for Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.10181","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:a181ecca9f0f9aa329b503223c5a4f5b1d4255a2855d3089b0a4e7bbbf9e0beb","target":"record","created_at":"2026-05-18T00:02:24Z","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":"8035f749866e2fce4c9d650799ace273917af4e7e96eba0c7a451e5d5e696025","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-24T04:08:22Z","title_canon_sha256":"dbb5fa0bcd106e51f893d1c67d92381cc46ad26c365d7fe92bd7414b6a466222"},"schema_version":"1.0","source":{"id":"1810.10181","kind":"arxiv","version":1}},"canonical_sha256":"3f12b2e04d3790f0bd0a35b5ce54c9b84d300bd842ab7deff32b63b27c5227ad","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3f12b2e04d3790f0bd0a35b5ce54c9b84d300bd842ab7deff32b63b27c5227ad","first_computed_at":"2026-05-18T00:02:24.001266Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:24.001266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BsvSOblzI/UY0xgh1OZuIBKvYJYG/Y3vHmmhZfoCzKh+vZwXn54WV9SW/L0Q9ZW1jmy7VY4dvpD/sJFm924bBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:24.001914Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.10181","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a181ecca9f0f9aa329b503223c5a4f5b1d4255a2855d3089b0a4e7bbbf9e0beb","sha256:5634d1da14a873987100e6c2d7c44507e3c35dc0686b7d38307564fdae1b2c41"],"state_sha256":"01dd6a7e939eb13da3c73b3380ba1428b988edd5a96b3a3a6d78fde01c6014bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QuVYoXUQET5/Ff7TPN38cSgkOUrS7xXXZUbnaIQXkOAR3mhXSSCl7Xhu6/97OsZ38RIGaLimSmiBkAnR7QEBCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T18:02:13.559842Z","bundle_sha256":"8280e22a5c153cae2e40990d38e33317a931600032929373ce2bd6d700adbf39"}}