{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:X3JWUEIL5TYUBN2MHEEND6CK2U","short_pith_number":"pith:X3JWUEIL","canonical_record":{"source":{"id":"1805.10163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-25T14:03:27Z","cross_cats_sorted":[],"title_canon_sha256":"8cc9bc7d07468310bf27ae50e23d9606a6c8e55db278bd7bfabc1d3263480144","abstract_canon_sha256":"975b5fa4cf13a0c71d7d10cd8bfb69b7dd4fb6f1ab49c75ba795c95afa4ebfd9"},"schema_version":"1.0"},"canonical_sha256":"bed36a110becf140b74c3908d1f84ad51c0482c751a45a329029c59195ff095d","source":{"kind":"arxiv","id":"1805.10163","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10163","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10163v1","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10163","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"pith_short_12","alias_value":"X3JWUEIL5TYU","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X3JWUEIL5TYUBN2M","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X3JWUEIL","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:X3JWUEIL5TYUBN2MHEEND6CK2U","target":"record","payload":{"canonical_record":{"source":{"id":"1805.10163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-25T14:03:27Z","cross_cats_sorted":[],"title_canon_sha256":"8cc9bc7d07468310bf27ae50e23d9606a6c8e55db278bd7bfabc1d3263480144","abstract_canon_sha256":"975b5fa4cf13a0c71d7d10cd8bfb69b7dd4fb6f1ab49c75ba795c95afa4ebfd9"},"schema_version":"1.0"},"canonical_sha256":"bed36a110becf140b74c3908d1f84ad51c0482c751a45a329029c59195ff095d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:58.122892Z","signature_b64":"2cJKOSP7P0D8EG+9wsgJ1Dn+GcaHUBU5V742kdWJgcGGtnFzMupcOZmkEoQwEHpO7jYnrkZKTyl918UrVc39BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bed36a110becf140b74c3908d1f84ad51c0482c751a45a329029c59195ff095d","last_reissued_at":"2026-05-18T00:14:58.122168Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:58.122168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.10163","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":"2026-05-18T00:14:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MWEKnWSlBOpXt2pO4byspVDORIv42xKts9oOH53XObceTGJvZ4oac0cnSOyk/Gs9YFs61lHWBVlrXNsBrRvFBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T05:01:22.173676Z"},"content_sha256":"6c1e3f0ba43cc3768f88a3aa387acbfb874facc3ee5ee4976f94db7be4578e91","schema_version":"1.0","event_id":"sha256:6c1e3f0ba43cc3768f88a3aa387acbfb874facc3ee5ee4976f94db7be4578e91"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:X3JWUEIL5TYUBN2MHEEND6CK2U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Context-Aware Neural Machine Translation Learns Anaphora Resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Elena Voita, Ivan Titov, Pavel Serdyukov, Rico Sennrich","submitted_at":"2018-05-25T14:03:27Z","abstract_excerpt":"Standard machine translation systems process sentences in isolation and hence ignore extra-sentential information, even though extended context can both prevent mistakes in ambiguous cases and improve translation coherence. We introduce a context-aware neural machine translation model designed in such way that the flow of information from the extended context to the translation model can be controlled and analyzed. We experiment with an English-Russian subtitles dataset, and observe that much of what is captured by our model deals with improving pronoun translation. We measure correspondences "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10163","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":"2026-05-18T00:14:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RW3eptIkjtnjtLDmK0GMm/rIiPIga1V/mYwCx269m+P9wj8NP1AkYsTmIrFUGOdCp2InudAFkOcpURAJQKh2DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T05:01:22.174033Z"},"content_sha256":"7093bf1fffb22cf278a11e3cfdfefedeed42d94fea1c21a17fd0fd6b0a1aa428","schema_version":"1.0","event_id":"sha256:7093bf1fffb22cf278a11e3cfdfefedeed42d94fea1c21a17fd0fd6b0a1aa428"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/bundle.json","state_url":"https://pith.science/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/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":"2026-05-30T05:01:22Z","links":{"resolver":"https://pith.science/pith/X3JWUEIL5TYUBN2MHEEND6CK2U","bundle":"https://pith.science/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/bundle.json","state":"https://pith.science/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X3JWUEIL5TYUBN2MHEEND6CK2U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:X3JWUEIL5TYUBN2MHEEND6CK2U","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":"975b5fa4cf13a0c71d7d10cd8bfb69b7dd4fb6f1ab49c75ba795c95afa4ebfd9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-25T14:03:27Z","title_canon_sha256":"8cc9bc7d07468310bf27ae50e23d9606a6c8e55db278bd7bfabc1d3263480144"},"schema_version":"1.0","source":{"id":"1805.10163","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10163","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10163v1","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10163","created_at":"2026-05-18T00:14:58Z"},{"alias_kind":"pith_short_12","alias_value":"X3JWUEIL5TYU","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X3JWUEIL5TYUBN2M","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X3JWUEIL","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:7093bf1fffb22cf278a11e3cfdfefedeed42d94fea1c21a17fd0fd6b0a1aa428","target":"graph","created_at":"2026-05-18T00:14:58Z","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":"Standard machine translation systems process sentences in isolation and hence ignore extra-sentential information, even though extended context can both prevent mistakes in ambiguous cases and improve translation coherence. We introduce a context-aware neural machine translation model designed in such way that the flow of information from the extended context to the translation model can be controlled and analyzed. We experiment with an English-Russian subtitles dataset, and observe that much of what is captured by our model deals with improving pronoun translation. We measure correspondences ","authors_text":"Elena Voita, Ivan Titov, Pavel Serdyukov, Rico Sennrich","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-25T14:03:27Z","title":"Context-Aware Neural Machine Translation Learns Anaphora Resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10163","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":"sha256:6c1e3f0ba43cc3768f88a3aa387acbfb874facc3ee5ee4976f94db7be4578e91","target":"record","created_at":"2026-05-18T00:14:58Z","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":"975b5fa4cf13a0c71d7d10cd8bfb69b7dd4fb6f1ab49c75ba795c95afa4ebfd9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-25T14:03:27Z","title_canon_sha256":"8cc9bc7d07468310bf27ae50e23d9606a6c8e55db278bd7bfabc1d3263480144"},"schema_version":"1.0","source":{"id":"1805.10163","kind":"arxiv","version":1}},"canonical_sha256":"bed36a110becf140b74c3908d1f84ad51c0482c751a45a329029c59195ff095d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bed36a110becf140b74c3908d1f84ad51c0482c751a45a329029c59195ff095d","first_computed_at":"2026-05-18T00:14:58.122168Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:58.122168Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2cJKOSP7P0D8EG+9wsgJ1Dn+GcaHUBU5V742kdWJgcGGtnFzMupcOZmkEoQwEHpO7jYnrkZKTyl918UrVc39BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:58.122892Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.10163","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6c1e3f0ba43cc3768f88a3aa387acbfb874facc3ee5ee4976f94db7be4578e91","sha256:7093bf1fffb22cf278a11e3cfdfefedeed42d94fea1c21a17fd0fd6b0a1aa428"],"state_sha256":"49de0382aff81f7633412a57c864cbefe2bd0d33c6cdc4d668d2b298bfc1a602"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6aIXuIIuJvae83mryXeHzsyrDsTAUjRdeHmlZkQrPO9UpXdfSS64HXGA2f4Aahyz63YBfrb8VaT42otI47rdDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T05:01:22.176069Z","bundle_sha256":"2a9f83a633504f2bcc58a02a785bccd1447d4d56cc6b3d08c41694bfc31a209b"}}