{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:BLBLOP5AZEYAOKPVJGM3C3X6BM","short_pith_number":"pith:BLBLOP5A","canonical_record":{"source":{"id":"1906.01130","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-03T23:47:43Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"eed20b5b794c2628f90db2693b03530775c8a38f688edb17f742021566ad7b4d","abstract_canon_sha256":"4414939f98693db2d89a897a441723a382e4f9dc640ca64596ed0c13c455b720"},"schema_version":"1.0"},"canonical_sha256":"0ac2b73fa0c9300729f54999b16efe0b132323fb47e25839b46a582c18f043f9","source":{"kind":"arxiv","id":"1906.01130","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01130","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01130v1","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01130","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"pith_short_12","alias_value":"BLBLOP5AZEYA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BLBLOP5AZEYAOKPV","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BLBLOP5A","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:BLBLOP5AZEYAOKPVJGM3C3X6BM","target":"record","payload":{"canonical_record":{"source":{"id":"1906.01130","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-03T23:47:43Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"eed20b5b794c2628f90db2693b03530775c8a38f688edb17f742021566ad7b4d","abstract_canon_sha256":"4414939f98693db2d89a897a441723a382e4f9dc640ca64596ed0c13c455b720"},"schema_version":"1.0"},"canonical_sha256":"0ac2b73fa0c9300729f54999b16efe0b132323fb47e25839b46a582c18f043f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:17.768249Z","signature_b64":"bd028hnc/qTStczhXyIZfB0tdUsUAlkoWhU4sA9rKp+Ac+jA3xyG6YXBiIGqv1M2eM8OPIwMQ3VXIGInevK5DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0ac2b73fa0c9300729f54999b16efe0b132323fb47e25839b46a582c18f043f9","last_reissued_at":"2026-05-17T23:44:17.767639Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:17.767639Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.01130","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":"2026-05-17T23:44:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8W76ZZ3QJvYfB1pKchkEj54On+I8Z4Z8dciMfEwGJWDAFa9FJvSmIeZK8pv6+MwsxvaMfK53eK64zDh9XhygDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T07:48:27.321125Z"},"content_sha256":"52220680deebd4826f5ef384ac69af3f84dc731caf399f4d02bd6790f412b37c","schema_version":"1.0","event_id":"sha256:52220680deebd4826f5ef384ac69af3f84dc731caf399f4d02bd6790f412b37c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:BLBLOP5AZEYAOKPVJGM3C3X6BM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dynamically Composing Domain-Data Selection with Clean-Data Selection by \"Co-Curricular Learning\" for Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Ciprian Chelba, Isaac Caswell, Wei Wang","submitted_at":"2019-06-03T23:47:43Z","abstract_excerpt":"Noise and domain are important aspects of data quality for neural machine translation. Existing research focus separately on domain-data selection, clean-data selection, or their static combination, leaving the dynamic interaction across them not explicitly examined. This paper introduces a \"co-curricular learning\" method to compose dynamic domain-data selection with dynamic clean-data selection, for transfer learning across both capabilities. We apply an EM-style optimization procedure to further refine the \"co-curriculum\". Experiment results and analysis with two domains demonstrate the effe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01130","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":"2026-05-17T23:44:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GBFdyEacZdkSxaajH3B++gV7MPS3DwSk4SfDWuyzrCXkrOKb0QfLZj2j+bLRWgE1p6/m9g2KsgGLTg6IiZtwDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T07:48:27.321850Z"},"content_sha256":"0a47c9002d121228447bcc3cf639ade311389584c6ff5fd086f295eabcc5cfad","schema_version":"1.0","event_id":"sha256:0a47c9002d121228447bcc3cf639ade311389584c6ff5fd086f295eabcc5cfad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/bundle.json","state_url":"https://pith.science/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/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":"2026-06-09T07:48:27Z","links":{"resolver":"https://pith.science/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM","bundle":"https://pith.science/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/bundle.json","state":"https://pith.science/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BLBLOP5AZEYAOKPVJGM3C3X6BM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BLBLOP5AZEYAOKPVJGM3C3X6BM","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":"4414939f98693db2d89a897a441723a382e4f9dc640ca64596ed0c13c455b720","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-03T23:47:43Z","title_canon_sha256":"eed20b5b794c2628f90db2693b03530775c8a38f688edb17f742021566ad7b4d"},"schema_version":"1.0","source":{"id":"1906.01130","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01130","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01130v1","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01130","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"pith_short_12","alias_value":"BLBLOP5AZEYA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BLBLOP5AZEYAOKPV","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BLBLOP5A","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:0a47c9002d121228447bcc3cf639ade311389584c6ff5fd086f295eabcc5cfad","target":"graph","created_at":"2026-05-17T23:44:17Z","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":"Noise and domain are important aspects of data quality for neural machine translation. Existing research focus separately on domain-data selection, clean-data selection, or their static combination, leaving the dynamic interaction across them not explicitly examined. This paper introduces a \"co-curricular learning\" method to compose dynamic domain-data selection with dynamic clean-data selection, for transfer learning across both capabilities. We apply an EM-style optimization procedure to further refine the \"co-curriculum\". Experiment results and analysis with two domains demonstrate the effe","authors_text":"Ciprian Chelba, Isaac Caswell, Wei Wang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-03T23:47:43Z","title":"Dynamically Composing Domain-Data Selection with Clean-Data Selection by \"Co-Curricular Learning\" for Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01130","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":"sha256:52220680deebd4826f5ef384ac69af3f84dc731caf399f4d02bd6790f412b37c","target":"record","created_at":"2026-05-17T23:44:17Z","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":"4414939f98693db2d89a897a441723a382e4f9dc640ca64596ed0c13c455b720","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-06-03T23:47:43Z","title_canon_sha256":"eed20b5b794c2628f90db2693b03530775c8a38f688edb17f742021566ad7b4d"},"schema_version":"1.0","source":{"id":"1906.01130","kind":"arxiv","version":1}},"canonical_sha256":"0ac2b73fa0c9300729f54999b16efe0b132323fb47e25839b46a582c18f043f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0ac2b73fa0c9300729f54999b16efe0b132323fb47e25839b46a582c18f043f9","first_computed_at":"2026-05-17T23:44:17.767639Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:17.767639Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bd028hnc/qTStczhXyIZfB0tdUsUAlkoWhU4sA9rKp+Ac+jA3xyG6YXBiIGqv1M2eM8OPIwMQ3VXIGInevK5DA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:17.768249Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.01130","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:52220680deebd4826f5ef384ac69af3f84dc731caf399f4d02bd6790f412b37c","sha256:0a47c9002d121228447bcc3cf639ade311389584c6ff5fd086f295eabcc5cfad"],"state_sha256":"34119130d640a106e1a6058589ce6b3cc0eaebe24437fef3f2fb5ca9cd979e18"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kCO/abbc+tiHuZKETAGRwqVvLwgkQ44wE9pEWGMi4khRPHvA2lQV9LApmVozn+y1e9azyG5TvZqECmb0St3LCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T07:48:27.326003Z","bundle_sha256":"ecb43a7b7166daadc02925501a137e0c463d45e8e4e036d2e154daf5d117172a"}}