{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HMSU2XHHGHU5CPDQFYLKGGT3EZ","short_pith_number":"pith:HMSU2XHH","schema_version":"1.0","canonical_sha256":"3b254d5ce731e9d13c702e16a31a7b26466803bbafe8e5c6a72c8d5f4e332b68","source":{"kind":"arxiv","id":"2309.11566","version":2},"attestation_state":"computed","paper":{"title":"SignBank+: Preparing a Multilingual Sign Language Dataset for Machine Translation Using Large Language Models","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Amit Moryossef, Zifan Jiang","submitted_at":"2023-09-20T18:08:28Z","abstract_excerpt":"We introduce SignBank+, a clean version of the SignBank dataset, optimized for machine translation between spoken language text and SignWriting, a phonetic sign language writing system. In addition to previous work that employs complex factorization techniques to enable translation between text and SignWriting, we show that a traditional text-to-text translation approach performs equally effectively on the cleaned SignBank+ dataset. Our evaluation results indicate that models trained on SignBank+ surpass those on the original dataset, establishing a new benchmark for SignWriting-based sign lan"},"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":"2309.11566","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-20T18:08:28Z","cross_cats_sorted":[],"title_canon_sha256":"fe59d6274801c156196bb803062e11561341fabfae90682240603979952ebcb9","abstract_canon_sha256":"d81444c253fd936499fcd634eb2788c3364d3180596a0fae0b295b26c2a6d98e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:03.462167Z","signature_b64":"QOZaFe3s7ciI2k8LR6Z9+yi5QI/Pkyu8+xD1bZMbTnP0uBVXCXi3UxMTQ/mZ+mpelJNfijxSIII1BAGSlvy9Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b254d5ce731e9d13c702e16a31a7b26466803bbafe8e5c6a72c8d5f4e332b68","last_reissued_at":"2026-07-05T07:59:03.461728Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:03.461728Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SignBank+: Preparing a Multilingual Sign Language Dataset for Machine Translation Using Large Language Models","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Amit Moryossef, Zifan Jiang","submitted_at":"2023-09-20T18:08:28Z","abstract_excerpt":"We introduce SignBank+, a clean version of the SignBank dataset, optimized for machine translation between spoken language text and SignWriting, a phonetic sign language writing system. In addition to previous work that employs complex factorization techniques to enable translation between text and SignWriting, we show that a traditional text-to-text translation approach performs equally effectively on the cleaned SignBank+ dataset. Our evaluation results indicate that models trained on SignBank+ surpass those on the original dataset, establishing a new benchmark for SignWriting-based sign lan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.11566","kind":"arxiv","version":2},"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/2309.11566/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":"2309.11566","created_at":"2026-07-05T07:59:03.461796+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.11566v2","created_at":"2026-07-05T07:59:03.461796+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.11566","created_at":"2026-07-05T07:59:03.461796+00:00"},{"alias_kind":"pith_short_12","alias_value":"HMSU2XHHGHU5","created_at":"2026-07-05T07:59:03.461796+00:00"},{"alias_kind":"pith_short_16","alias_value":"HMSU2XHHGHU5CPDQ","created_at":"2026-07-05T07:59:03.461796+00:00"},{"alias_kind":"pith_short_8","alias_value":"HMSU2XHH","created_at":"2026-07-05T07:59:03.461796+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.18183","citing_title":"Leveraging Large Language Models for Accurate Sign Language Translation in Low-Resource Scenarios","ref_index":27,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ","json":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ.json","graph_json":"https://pith.science/api/pith-number/HMSU2XHHGHU5CPDQFYLKGGT3EZ/graph.json","events_json":"https://pith.science/api/pith-number/HMSU2XHHGHU5CPDQFYLKGGT3EZ/events.json","paper":"https://pith.science/paper/HMSU2XHH"},"agent_actions":{"view_html":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ","download_json":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ.json","view_paper":"https://pith.science/paper/HMSU2XHH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.11566&json=true","fetch_graph":"https://pith.science/api/pith-number/HMSU2XHHGHU5CPDQFYLKGGT3EZ/graph.json","fetch_events":"https://pith.science/api/pith-number/HMSU2XHHGHU5CPDQFYLKGGT3EZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ/action/storage_attestation","attest_author":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ/action/author_attestation","sign_citation":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ/action/citation_signature","submit_replication":"https://pith.science/pith/HMSU2XHHGHU5CPDQFYLKGGT3EZ/action/replication_record"}},"created_at":"2026-07-05T07:59:03.461796+00:00","updated_at":"2026-07-05T07:59:03.461796+00:00"}