{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HP64FMPHG6GGZUYDWZYN5YUMLD","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":"2c66a3dfb346fb8c8a394ebb6fc579fe1490567b89ab6b9fe8f82893ad3cbef6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T21:12:39Z","title_canon_sha256":"a9f30a7a97f196a5047b0e677a224661584b785f6d79b3d09bc32f5dba92f96c"},"schema_version":"1.0","source":{"id":"2412.20584","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.20584","created_at":"2026-07-05T11:13:17Z"},{"alias_kind":"arxiv_version","alias_value":"2412.20584v2","created_at":"2026-07-05T11:13:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20584","created_at":"2026-07-05T11:13:17Z"},{"alias_kind":"pith_short_12","alias_value":"HP64FMPHG6GG","created_at":"2026-07-05T11:13:17Z"},{"alias_kind":"pith_short_16","alias_value":"HP64FMPHG6GGZUYD","created_at":"2026-07-05T11:13:17Z"},{"alias_kind":"pith_short_8","alias_value":"HP64FMPH","created_at":"2026-07-05T11:13:17Z"}],"graph_snapshots":[{"event_id":"sha256:ec875ae29689a379e0525f6bfe651598a9b1faf4d79a656382376cc36130d8af","target":"graph","created_at":"2026-07-05T11:13:17Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.20584/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"No-resource languages - those with minimal or no digital representation - pose unique challenges for machine translation (MT). Unlike low-resource languages, which rely on limited but existent corpora, no-resource languages often have fewer than 100 sentences available for training. This work explores the problem of no-resource translation through three distinct workflows: fine-tuning of translation-specific models, in-context learning with large language models (LLMs) using chain-of-reasoning prompting, and direct prompting without reasoning. Using Owens Valley Paiute as a case study, we demo","authors_text":"Madhavendra Thakur","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T21:12:39Z","title":"Towards Neural No-Resource Language Translation: A Comparative Evaluation of Approaches"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20584","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":"sha256:03f85725b96923ec442e8797288d5cd69e553f82aba6daed4277cb2bf9c9edec","target":"record","created_at":"2026-07-05T11:13:17Z","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":"2c66a3dfb346fb8c8a394ebb6fc579fe1490567b89ab6b9fe8f82893ad3cbef6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T21:12:39Z","title_canon_sha256":"a9f30a7a97f196a5047b0e677a224661584b785f6d79b3d09bc32f5dba92f96c"},"schema_version":"1.0","source":{"id":"2412.20584","kind":"arxiv","version":2}},"canonical_sha256":"3bfdc2b1e7378c6cd303b670dee28c58f8c64acf1b23b34a9387a0dd0cbd3fae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3bfdc2b1e7378c6cd303b670dee28c58f8c64acf1b23b34a9387a0dd0cbd3fae","first_computed_at":"2026-07-05T11:13:17.906021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:17.906021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4c8Srnrx2K4e7qiGo6jnq4v0mtdHbfu3u4wjkkRsTopnrNHxBUOxjcEUmNj4DrRb0DaJjSH7EdRGqvRM6JJlDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:17.906499Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.20584","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:03f85725b96923ec442e8797288d5cd69e553f82aba6daed4277cb2bf9c9edec","sha256:ec875ae29689a379e0525f6bfe651598a9b1faf4d79a656382376cc36130d8af"],"state_sha256":"56f99e4d7dc5e411045ee064dc919a7e3baffeb27f1208cd4d7866b48aae208f"}