{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HC4FDMRZZ6CMYVKJWI6NBUPVX3","short_pith_number":"pith:HC4FDMRZ","canonical_record":{"source":{"id":"2506.00748","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-31T23:27:07Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"96932522e7d1b183b0e586347c3b000b8fbd024c5b08d1c58faef49e62aea356","abstract_canon_sha256":"3bb1c4298a986606e2c3b947903fd158b7f87a912afe4e084f4e7204827085f6"},"schema_version":"1.0"},"canonical_sha256":"38b851b239cf84cc5549b23cd0d1f5befc05398086f82e752f283212ae22db7a","source":{"kind":"arxiv","id":"2506.00748","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00748","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00748v1","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00748","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_12","alias_value":"HC4FDMRZZ6CM","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_16","alias_value":"HC4FDMRZZ6CMYVKJ","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_8","alias_value":"HC4FDMRZ","created_at":"2026-07-05T11:13:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HC4FDMRZZ6CMYVKJWI6NBUPVX3","target":"record","payload":{"canonical_record":{"source":{"id":"2506.00748","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-31T23:27:07Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"96932522e7d1b183b0e586347c3b000b8fbd024c5b08d1c58faef49e62aea356","abstract_canon_sha256":"3bb1c4298a986606e2c3b947903fd158b7f87a912afe4e084f4e7204827085f6"},"schema_version":"1.0"},"canonical_sha256":"38b851b239cf84cc5549b23cd0d1f5befc05398086f82e752f283212ae22db7a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:39.874701Z","signature_b64":"NpDBplayHt7NoUn9Us0ts3wN+6t/ULpr4TtlHQKku0svzZq4QliuUNgOXjWhiaCsD7GoEpxePqJXElO2977QCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38b851b239cf84cc5549b23cd0d1f5befc05398086f82e752f283212ae22db7a","last_reissued_at":"2026-07-05T11:13:39.874165Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:39.874165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.00748","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":"2026-07-05T11:13:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZMGbS0jTLJ9QExVKmy87a3SgzbZnHoxPEyELx/t1qVC35+5Llv8CkWH8/OOpFFGqJYnyBcv57xDhF+5sIdGYDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T01:15:26.288716Z"},"content_sha256":"bb4b75f629dd116063a889a6b2df5d2847e1a21793a8b48416d342a00b232dc5","schema_version":"1.0","event_id":"sha256:bb4b75f629dd116063a889a6b2df5d2847e1a21793a8b48416d342a00b232dc5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HC4FDMRZZ6CMYVKJWI6NBUPVX3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.CL","authors_text":"Ali Emami, Pardis Sadat Zahraei","submitted_at":"2025-05-31T23:27:07Z","abstract_excerpt":"Addressing gender bias and maintaining logical coherence in machine translation remains challenging, particularly when translating between natural gender languages, like English, and genderless languages, such as Persian, Indonesian, and Finnish. We introduce the Translate-with-Care (TWC) dataset, comprising 3,950 challenging scenarios across six low- to mid-resource languages, to assess translation systems' performance. Our analysis of diverse technologies, including GPT-4, mBART-50, NLLB-200, and Google Translate, reveals a universal struggle in translating genderless content, resulting in g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00748","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/2506.00748/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:13:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K2MCMc04Nb5JROsBna5bBxwIpRPjd9+geQkI3C0N90MLx7BV9yGt6el0t75Z1iA68XfVa1u0Lu7sl2UJDX30Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T01:15:26.289233Z"},"content_sha256":"1b014986b9e5fee2c2eff826cafb4df12ff694647a29f93dc3b44f95cfb86e0e","schema_version":"1.0","event_id":"sha256:1b014986b9e5fee2c2eff826cafb4df12ff694647a29f93dc3b44f95cfb86e0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/bundle.json","state_url":"https://pith.science/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/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":"2026-08-08T01:15:26Z","links":{"resolver":"https://pith.science/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3","bundle":"https://pith.science/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/bundle.json","state":"https://pith.science/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HC4FDMRZZ6CMYVKJWI6NBUPVX3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HC4FDMRZZ6CMYVKJWI6NBUPVX3","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":"3bb1c4298a986606e2c3b947903fd158b7f87a912afe4e084f4e7204827085f6","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-31T23:27:07Z","title_canon_sha256":"96932522e7d1b183b0e586347c3b000b8fbd024c5b08d1c58faef49e62aea356"},"schema_version":"1.0","source":{"id":"2506.00748","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00748","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00748v1","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00748","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_12","alias_value":"HC4FDMRZZ6CM","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_16","alias_value":"HC4FDMRZZ6CMYVKJ","created_at":"2026-07-05T11:13:39Z"},{"alias_kind":"pith_short_8","alias_value":"HC4FDMRZ","created_at":"2026-07-05T11:13:39Z"}],"graph_snapshots":[{"event_id":"sha256:1b014986b9e5fee2c2eff826cafb4df12ff694647a29f93dc3b44f95cfb86e0e","target":"graph","created_at":"2026-07-05T11:13:39Z","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/2506.00748/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Addressing gender bias and maintaining logical coherence in machine translation remains challenging, particularly when translating between natural gender languages, like English, and genderless languages, such as Persian, Indonesian, and Finnish. We introduce the Translate-with-Care (TWC) dataset, comprising 3,950 challenging scenarios across six low- to mid-resource languages, to assess translation systems' performance. Our analysis of diverse technologies, including GPT-4, mBART-50, NLLB-200, and Google Translate, reveals a universal struggle in translating genderless content, resulting in g","authors_text":"Ali Emami, Pardis Sadat Zahraei","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-31T23:27:07Z","title":"Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00748","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:bb4b75f629dd116063a889a6b2df5d2847e1a21793a8b48416d342a00b232dc5","target":"record","created_at":"2026-07-05T11:13:39Z","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":"3bb1c4298a986606e2c3b947903fd158b7f87a912afe4e084f4e7204827085f6","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-31T23:27:07Z","title_canon_sha256":"96932522e7d1b183b0e586347c3b000b8fbd024c5b08d1c58faef49e62aea356"},"schema_version":"1.0","source":{"id":"2506.00748","kind":"arxiv","version":1}},"canonical_sha256":"38b851b239cf84cc5549b23cd0d1f5befc05398086f82e752f283212ae22db7a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38b851b239cf84cc5549b23cd0d1f5befc05398086f82e752f283212ae22db7a","first_computed_at":"2026-07-05T11:13:39.874165Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:39.874165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NpDBplayHt7NoUn9Us0ts3wN+6t/ULpr4TtlHQKku0svzZq4QliuUNgOXjWhiaCsD7GoEpxePqJXElO2977QCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:39.874701Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.00748","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb4b75f629dd116063a889a6b2df5d2847e1a21793a8b48416d342a00b232dc5","sha256:1b014986b9e5fee2c2eff826cafb4df12ff694647a29f93dc3b44f95cfb86e0e"],"state_sha256":"ef658caa25aebbc1aa7f50ddb4e8cd2478d17d826611133aa1e5343013992ea4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MVuoAwaSCm87RpsQALUB8/mmzQYyGk1K5J4y6MFWebUIBUV8O1rYDsvur0qGvwX9pBrkh1Or9TNWwa9sc0gWAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T01:15:26.292915Z","bundle_sha256":"96d77f1d17eeb2b43265af1060d8032851800688cdc624e0fe0e12e1750ee3e8"}}