{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:TWDLPWIVLV3XPLM3YQQJOLM7LY","short_pith_number":"pith:TWDLPWIV","schema_version":"1.0","canonical_sha256":"9d86b7d9155d7777ad9bc420972d9f5e32edc349d099e6fff93ec0f03e94d6e1","source":{"kind":"arxiv","id":"2607.29355","version":1},"attestation_state":"computed","paper":{"title":"Cross-Lingual Transfer for Machine Translation in Turkic Languages","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cagri Toraman, Mehmet Mert Dalkilic, Omer Burak Cinar","submitted_at":"2026-07-31T12:42:17Z","abstract_excerpt":"Cross-lingual transfer is central to low-resource machine translation, but its behavior within closely related language families remains insufficiently characterized. We study transfer among five Turkic languages; Turkish, Azerbaijani, Uzbek, Kazakh, and Kyrgyz; using pairwise transfer matrices. In this setting, each model is fine-tuned with one transfer source and evaluated on a different transfer target while the translation target remains the same. Across mT5 experiments, we find that transfer is strongest between closely related Turkic pairs, especially Turkish-Azerbaijani and Kazakh-Kyrgy"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.29355","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T12:42:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6c1eecd8c2a68e47c01ff02c8948cfc974d822d09f8911541acbe1538f09df9c","abstract_canon_sha256":"c6f5b6cea1ae08b1cd5888fbbd3808f6ec282db978a536ce8721b22178722cb3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:33:15.573175Z","signature_b64":"tOlsEutwrS/jwqZm3gffq/iGNc28+zuuhkgDaUZp6umkx/QhqEr865v+MlJMsHdhM0T4G12BRpuyUt3MuM4PCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d86b7d9155d7777ad9bc420972d9f5e32edc349d099e6fff93ec0f03e94d6e1","last_reissued_at":"2026-08-03T01:33:15.571518Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:33:15.571518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cross-Lingual Transfer for Machine Translation in Turkic Languages","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cagri Toraman, Mehmet Mert Dalkilic, Omer Burak Cinar","submitted_at":"2026-07-31T12:42:17Z","abstract_excerpt":"Cross-lingual transfer is central to low-resource machine translation, but its behavior within closely related language families remains insufficiently characterized. We study transfer among five Turkic languages; Turkish, Azerbaijani, Uzbek, Kazakh, and Kyrgyz; using pairwise transfer matrices. In this setting, each model is fine-tuned with one transfer source and evaluated on a different transfer target while the translation target remains the same. Across mT5 experiments, we find that transfer is strongest between closely related Turkic pairs, especially Turkish-Azerbaijani and Kazakh-Kyrgy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29355","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.29355/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.29355","created_at":"2026-08-03T01:33:15.572385+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29355v1","created_at":"2026-08-03T01:33:15.572385+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29355","created_at":"2026-08-03T01:33:15.572385+00:00"},{"alias_kind":"pith_short_12","alias_value":"TWDLPWIVLV3X","created_at":"2026-08-03T01:33:15.572385+00:00"},{"alias_kind":"pith_short_16","alias_value":"TWDLPWIVLV3XPLM3","created_at":"2026-08-03T01:33:15.572385+00:00"},{"alias_kind":"pith_short_8","alias_value":"TWDLPWIV","created_at":"2026-08-03T01:33:15.572385+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY","json":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY.json","graph_json":"https://pith.science/api/pith-number/TWDLPWIVLV3XPLM3YQQJOLM7LY/graph.json","events_json":"https://pith.science/api/pith-number/TWDLPWIVLV3XPLM3YQQJOLM7LY/events.json","paper":"https://pith.science/paper/TWDLPWIV"},"agent_actions":{"view_html":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY","download_json":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY.json","view_paper":"https://pith.science/paper/TWDLPWIV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29355&json=true","fetch_graph":"https://pith.science/api/pith-number/TWDLPWIVLV3XPLM3YQQJOLM7LY/graph.json","fetch_events":"https://pith.science/api/pith-number/TWDLPWIVLV3XPLM3YQQJOLM7LY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY/action/storage_attestation","attest_author":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY/action/author_attestation","sign_citation":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY/action/citation_signature","submit_replication":"https://pith.science/pith/TWDLPWIVLV3XPLM3YQQJOLM7LY/action/replication_record"}},"created_at":"2026-08-03T01:33:15.572385+00:00","updated_at":"2026-08-03T01:33:15.572385+00:00"}