{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:P2T5JQDKSSBCNKRUIPGGSKNUP4","short_pith_number":"pith:P2T5JQDK","canonical_record":{"source":{"id":"1903.00149","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-03-01T03:57:15Z","cross_cats_sorted":[],"title_canon_sha256":"dad140dab8558947112cd5bcf5abe5eb84dbed0213ce31ac6bf05cced9184337","abstract_canon_sha256":"43fb65a5f3f3ac2a22e6adbca2e284ec65d401800dc068c1296ee6483c848896"},"schema_version":"1.0"},"canonical_sha256":"7ea7d4c06a948226aa3443cc6929b47f2680570fe59eafca3007c559bb5baf6a","source":{"kind":"arxiv","id":"1903.00149","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00149","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00149v1","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00149","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"pith_short_12","alias_value":"P2T5JQDKSSBC","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"P2T5JQDKSSBCNKRU","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"P2T5JQDK","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:P2T5JQDKSSBCNKRUIPGGSKNUP4","target":"record","payload":{"canonical_record":{"source":{"id":"1903.00149","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-03-01T03:57:15Z","cross_cats_sorted":[],"title_canon_sha256":"dad140dab8558947112cd5bcf5abe5eb84dbed0213ce31ac6bf05cced9184337","abstract_canon_sha256":"43fb65a5f3f3ac2a22e6adbca2e284ec65d401800dc068c1296ee6483c848896"},"schema_version":"1.0"},"canonical_sha256":"7ea7d4c06a948226aa3443cc6929b47f2680570fe59eafca3007c559bb5baf6a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:20.738571Z","signature_b64":"2+LDOPe1xVFC8ezhesyMG0UE8CFk3RfF2R8PfylDTOeYneSO/L25eqxuhxgORxCmM7Jcx10MHcE2zgWs9UWYCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ea7d4c06a948226aa3443cc6929b47f2680570fe59eafca3007c559bb5baf6a","last_reissued_at":"2026-05-17T23:52:20.737801Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:20.737801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.00149","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":"2026-05-17T23:52:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Cdkk7k0ddrenpmf2caE8sKLRRhvcBfhVX9PiaAzZ6q5tjsNBeBRhHRtTVSZXySsooFSzGlnliqOKboAozLNABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T11:38:33.462537Z"},"content_sha256":"bdb4e4ceb585dd487673f6c1eccaff0ee0aef77c1d8ce163edabb78fd1776f8d","schema_version":"1.0","event_id":"sha256:bdb4e4ceb585dd487673f6c1eccaff0ee0aef77c1d8ce163edabb78fd1776f8d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:P2T5JQDKSSBCNKRUIPGGSKNUP4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Chinese-Japanese Unsupervised Neural Machine Translation Using Sub-character Level Information","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Longtu Zhang, Mamoru Komachi","submitted_at":"2019-03-01T03:57:15Z","abstract_excerpt":"Unsupervised neural machine translation (UNMT) requires only monolingual data of similar language pairs during training and can produce bi-directional translation models with relatively good performance on alphabetic languages (Lample et al., 2018). However, no research has been done to logographic language pairs. This study focuses on Chinese-Japanese UNMT trained by data containing sub-character (ideograph or stroke) level information which is decomposed from character level data. BLEU scores of both character and sub-character level systems were compared against each other and the results s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00149","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":"2026-05-17T23:52:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"COskK07HHoKAERPzg9yII8lLi5N92RQtRybc7oDNNAxbROzb7zrBU0FtS2WZF718FEy4Hcq9Z8VU/xiXVzWNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T11:38:33.462879Z"},"content_sha256":"fda8f19d9ae6ddab988fb899eade6e1413be0b09aa07f3fc4ef8f83616f6d0be","schema_version":"1.0","event_id":"sha256:fda8f19d9ae6ddab988fb899eade6e1413be0b09aa07f3fc4ef8f83616f6d0be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/bundle.json","state_url":"https://pith.science/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/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":"2026-06-26T11:38:33Z","links":{"resolver":"https://pith.science/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4","bundle":"https://pith.science/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/bundle.json","state":"https://pith.science/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P2T5JQDKSSBCNKRUIPGGSKNUP4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:P2T5JQDKSSBCNKRUIPGGSKNUP4","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":"43fb65a5f3f3ac2a22e6adbca2e284ec65d401800dc068c1296ee6483c848896","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-03-01T03:57:15Z","title_canon_sha256":"dad140dab8558947112cd5bcf5abe5eb84dbed0213ce31ac6bf05cced9184337"},"schema_version":"1.0","source":{"id":"1903.00149","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00149","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00149v1","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00149","created_at":"2026-05-17T23:52:20Z"},{"alias_kind":"pith_short_12","alias_value":"P2T5JQDKSSBC","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"P2T5JQDKSSBCNKRU","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"P2T5JQDK","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:fda8f19d9ae6ddab988fb899eade6e1413be0b09aa07f3fc4ef8f83616f6d0be","target":"graph","created_at":"2026-05-17T23:52:20Z","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":"Unsupervised neural machine translation (UNMT) requires only monolingual data of similar language pairs during training and can produce bi-directional translation models with relatively good performance on alphabetic languages (Lample et al., 2018). However, no research has been done to logographic language pairs. This study focuses on Chinese-Japanese UNMT trained by data containing sub-character (ideograph or stroke) level information which is decomposed from character level data. BLEU scores of both character and sub-character level systems were compared against each other and the results s","authors_text":"Longtu Zhang, Mamoru Komachi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-03-01T03:57:15Z","title":"Chinese-Japanese Unsupervised Neural Machine Translation Using Sub-character Level Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00149","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:bdb4e4ceb585dd487673f6c1eccaff0ee0aef77c1d8ce163edabb78fd1776f8d","target":"record","created_at":"2026-05-17T23:52:20Z","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":"43fb65a5f3f3ac2a22e6adbca2e284ec65d401800dc068c1296ee6483c848896","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-03-01T03:57:15Z","title_canon_sha256":"dad140dab8558947112cd5bcf5abe5eb84dbed0213ce31ac6bf05cced9184337"},"schema_version":"1.0","source":{"id":"1903.00149","kind":"arxiv","version":1}},"canonical_sha256":"7ea7d4c06a948226aa3443cc6929b47f2680570fe59eafca3007c559bb5baf6a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ea7d4c06a948226aa3443cc6929b47f2680570fe59eafca3007c559bb5baf6a","first_computed_at":"2026-05-17T23:52:20.737801Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:20.737801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2+LDOPe1xVFC8ezhesyMG0UE8CFk3RfF2R8PfylDTOeYneSO/L25eqxuhxgORxCmM7Jcx10MHcE2zgWs9UWYCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:20.738571Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.00149","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bdb4e4ceb585dd487673f6c1eccaff0ee0aef77c1d8ce163edabb78fd1776f8d","sha256:fda8f19d9ae6ddab988fb899eade6e1413be0b09aa07f3fc4ef8f83616f6d0be"],"state_sha256":"5b1bd330a0282b5fc2ef07aa543402aa518b22a8146d698e1cef57ffc4f6590c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZFBE23KoYdKIpwEpowggRjQn7UWWSWNI39PcSaPtsLib80okPKxw39XWo7RxYKYS6fRfUZa83AVtZ7yrwHESDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T11:38:33.464852Z","bundle_sha256":"49f3ce3da9283c0712c4c6f3e7aee3632a676eab45c8f19ba1ebb8e1df399599"}}