{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:V57OZ7EY2JM6VHOLNJPZZLNGQQ","short_pith_number":"pith:V57OZ7EY","canonical_record":{"source":{"id":"1409.1259","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-09-03T21:03:41Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2d8917e3f0f092fd34a49f3f64c430e838d104cf84723588a64cf44765506b13","abstract_canon_sha256":"cf05895617c285fe0420bafb5be151f6e4a20f236cc3d5e3b40eac3e96907cb6"},"schema_version":"1.0"},"canonical_sha256":"af7eecfc98d259ea9dcb6a5f9cada684137e5c080a8f140c0db4808c0b1dda9e","source":{"kind":"arxiv","id":"1409.1259","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1409.1259","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"arxiv_version","alias_value":"1409.1259v2","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.1259","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"pith_short_12","alias_value":"V57OZ7EY2JM6","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"V57OZ7EY2JM6VHOL","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"V57OZ7EY","created_at":"2026-05-18T12:28:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:V57OZ7EY2JM6VHOLNJPZZLNGQQ","target":"record","payload":{"canonical_record":{"source":{"id":"1409.1259","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-09-03T21:03:41Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2d8917e3f0f092fd34a49f3f64c430e838d104cf84723588a64cf44765506b13","abstract_canon_sha256":"cf05895617c285fe0420bafb5be151f6e4a20f236cc3d5e3b40eac3e96907cb6"},"schema_version":"1.0"},"canonical_sha256":"af7eecfc98d259ea9dcb6a5f9cada684137e5c080a8f140c0db4808c0b1dda9e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:40:55.379351Z","signature_b64":"5QaLIrRqolJ06cjk31ieVp9mAAL8c01xbeRSZYCGU9TztcHKzR4pFa5zxSNVgC/g9BJ9XA1YDUXJ2Dxz9aG6CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af7eecfc98d259ea9dcb6a5f9cada684137e5c080a8f140c0db4808c0b1dda9e","last_reissued_at":"2026-05-18T02:40:55.378773Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:40:55.378773Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1409.1259","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":"2026-05-18T02:40:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8O9ajj6xqwYjIt7jSjVxxYS9jMvLARnwou8+B3wB9AYyaKkFar3YjlnnYNC3Ynh5CyN87XRsXBlvRsptHmf/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T17:57:04.070723Z"},"content_sha256":"6172da6c3b70f653ebb92c7b4459440428e89258db1b67f4c175f91675c85907","schema_version":"1.0","event_id":"sha256:6172da6c3b70f653ebb92c7b4459440428e89258db1b67f4c175f91675c85907"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:V57OZ7EY2JM6VHOLNJPZZLNGQQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Properties of Neural Machine Translation: Encoder-Decoder Approaches","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.CL","authors_text":"Bart van Merrienboer, Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio","submitted_at":"2014-09-03T21:03:41Z","abstract_excerpt":"Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a decoder. The encoder extracts a fixed-length representation from a variable-length input sentence, and the decoder generates a correct translation from this representation. In this paper, we focus on analyzing the properties of the neural machine translation using two models; RNN Encoder--Decoder and a newly proposed gated recursive convolutional neural network. We show that the neural machine transla"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.1259","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":"2026-05-18T02:40:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"km+WqZ7mThdhrkaZhuXVcgx2TlXKJd69OPkKaXeRcWJURF0KCaHBfm/0JVXOK11vBmfeoEB9HFCwpAlJrI1WBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T17:57:04.071374Z"},"content_sha256":"91ae963efd8355b65e5197e2762aafa781cd8a4ee29c35d913c2579db1fe6041","schema_version":"1.0","event_id":"sha256:91ae963efd8355b65e5197e2762aafa781cd8a4ee29c35d913c2579db1fe6041"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/bundle.json","state_url":"https://pith.science/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/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":"2026-06-07T17:57:04Z","links":{"resolver":"https://pith.science/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ","bundle":"https://pith.science/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/bundle.json","state":"https://pith.science/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V57OZ7EY2JM6VHOLNJPZZLNGQQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:V57OZ7EY2JM6VHOLNJPZZLNGQQ","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":"cf05895617c285fe0420bafb5be151f6e4a20f236cc3d5e3b40eac3e96907cb6","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-09-03T21:03:41Z","title_canon_sha256":"2d8917e3f0f092fd34a49f3f64c430e838d104cf84723588a64cf44765506b13"},"schema_version":"1.0","source":{"id":"1409.1259","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1409.1259","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"arxiv_version","alias_value":"1409.1259v2","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.1259","created_at":"2026-05-18T02:40:55Z"},{"alias_kind":"pith_short_12","alias_value":"V57OZ7EY2JM6","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"V57OZ7EY2JM6VHOL","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"V57OZ7EY","created_at":"2026-05-18T12:28:52Z"}],"graph_snapshots":[{"event_id":"sha256:91ae963efd8355b65e5197e2762aafa781cd8a4ee29c35d913c2579db1fe6041","target":"graph","created_at":"2026-05-18T02:40:55Z","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":"Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a decoder. The encoder extracts a fixed-length representation from a variable-length input sentence, and the decoder generates a correct translation from this representation. In this paper, we focus on analyzing the properties of the neural machine translation using two models; RNN Encoder--Decoder and a newly proposed gated recursive convolutional neural network. We show that the neural machine transla","authors_text":"Bart van Merrienboer, Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-09-03T21:03:41Z","title":"On the Properties of Neural Machine Translation: Encoder-Decoder Approaches"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.1259","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":"sha256:6172da6c3b70f653ebb92c7b4459440428e89258db1b67f4c175f91675c85907","target":"record","created_at":"2026-05-18T02:40:55Z","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":"cf05895617c285fe0420bafb5be151f6e4a20f236cc3d5e3b40eac3e96907cb6","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-09-03T21:03:41Z","title_canon_sha256":"2d8917e3f0f092fd34a49f3f64c430e838d104cf84723588a64cf44765506b13"},"schema_version":"1.0","source":{"id":"1409.1259","kind":"arxiv","version":2}},"canonical_sha256":"af7eecfc98d259ea9dcb6a5f9cada684137e5c080a8f140c0db4808c0b1dda9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af7eecfc98d259ea9dcb6a5f9cada684137e5c080a8f140c0db4808c0b1dda9e","first_computed_at":"2026-05-18T02:40:55.378773Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:40:55.378773Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5QaLIrRqolJ06cjk31ieVp9mAAL8c01xbeRSZYCGU9TztcHKzR4pFa5zxSNVgC/g9BJ9XA1YDUXJ2Dxz9aG6CQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:40:55.379351Z","signed_message":"canonical_sha256_bytes"},"source_id":"1409.1259","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6172da6c3b70f653ebb92c7b4459440428e89258db1b67f4c175f91675c85907","sha256:91ae963efd8355b65e5197e2762aafa781cd8a4ee29c35d913c2579db1fe6041"],"state_sha256":"c7fbcd2a51fe382b727e993679cd18875b2cda1a6d31499ff849e9956c35852f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AZQRVl61Pjoab0HVFSLsEJIrCVLWbaP44bepGJRkuGmwICF8tnkvyNWOGt1/mP0BK2ZhQmt898Ne+0j2DiVHBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T17:57:04.075268Z","bundle_sha256":"a0326b9d99b00c88a5e84cb552b1e4f891f345c027a0c9747738efc6f20d6447"}}