{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ELVRHMGEPUC63ZX75A3XHQMIQ4","short_pith_number":"pith:ELVRHMGE","schema_version":"1.0","canonical_sha256":"22eb13b0c47d05ede6ffe83773c1888734172821093a1e12691749848b0bcfd0","source":{"kind":"arxiv","id":"2510.17476","version":2},"attestation_state":"computed","paper":{"title":"Zoom In Disparities in Healthcare LLM Q&A","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Burcu Sayin, Cesare Barbera, Frederik M. Labont\\'e, Ipek Baris Schlicht, Lucie Flek, Marco Viviani, Paolo Rosso, Zhixue Zhao","submitted_at":"2025-10-20T12:19:08Z","abstract_excerpt":"Equitable access to reliable health information is vital when integrating AI into healthcare. Yet, information quality varies across languages, raising concerns about the reliability and consistency of multilingual Large Language Models (LLMs). We systematically examine cross-lingual disparities in pre-training source and factuality alignment in LLM answers for multilingual healthcare Q&A across English, German, Turkish, Chinese (Mandarin), and Italian. We (i) constructed Multilingual Wiki Health Care (MultiWikiHealthCare), a multilingual dataset from Wikipedia; (ii) analyzed cross-lingual hea"},"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":"2510.17476","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-20T12:19:08Z","cross_cats_sorted":[],"title_canon_sha256":"def77de25c5611058a3e6b6d86df10706213af299cbad03cf34cd71a6acde917","abstract_canon_sha256":"a7e11f9ec0b0f5f1f38b1e7b0cc99dfa3a98300007ba2ad0683d02b1caed087a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-09T01:19:38.172860Z","signature_b64":"8DiDRUugi8vbc429uXDs6rIPsOb6RQyeZ1eHi5g1iaELl4O42yf5ORCPV3Rk4QxdY/H9n/5dk5gEs1Hg/XhOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22eb13b0c47d05ede6ffe83773c1888734172821093a1e12691749848b0bcfd0","last_reissued_at":"2026-07-09T01:19:38.172364Z","signature_status":"signed_v1","first_computed_at":"2026-07-09T01:19:38.172364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Zoom In Disparities in Healthcare LLM Q&A","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Burcu Sayin, Cesare Barbera, Frederik M. Labont\\'e, Ipek Baris Schlicht, Lucie Flek, Marco Viviani, Paolo Rosso, Zhixue Zhao","submitted_at":"2025-10-20T12:19:08Z","abstract_excerpt":"Equitable access to reliable health information is vital when integrating AI into healthcare. Yet, information quality varies across languages, raising concerns about the reliability and consistency of multilingual Large Language Models (LLMs). We systematically examine cross-lingual disparities in pre-training source and factuality alignment in LLM answers for multilingual healthcare Q&A across English, German, Turkish, Chinese (Mandarin), and Italian. We (i) constructed Multilingual Wiki Health Care (MultiWikiHealthCare), a multilingual dataset from Wikipedia; (ii) analyzed cross-lingual hea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.17476","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/2510.17476/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":"2510.17476","created_at":"2026-07-09T01:19:38.172433+00:00"},{"alias_kind":"arxiv_version","alias_value":"2510.17476v2","created_at":"2026-07-09T01:19:38.172433+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.17476","created_at":"2026-07-09T01:19:38.172433+00:00"},{"alias_kind":"pith_short_12","alias_value":"ELVRHMGEPUC6","created_at":"2026-07-09T01:19:38.172433+00:00"},{"alias_kind":"pith_short_16","alias_value":"ELVRHMGEPUC63ZX7","created_at":"2026-07-09T01:19:38.172433+00:00"},{"alias_kind":"pith_short_8","alias_value":"ELVRHMGE","created_at":"2026-07-09T01:19:38.172433+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/ELVRHMGEPUC63ZX75A3XHQMIQ4","json":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4.json","graph_json":"https://pith.science/api/pith-number/ELVRHMGEPUC63ZX75A3XHQMIQ4/graph.json","events_json":"https://pith.science/api/pith-number/ELVRHMGEPUC63ZX75A3XHQMIQ4/events.json","paper":"https://pith.science/paper/ELVRHMGE"},"agent_actions":{"view_html":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4","download_json":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4.json","view_paper":"https://pith.science/paper/ELVRHMGE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2510.17476&json=true","fetch_graph":"https://pith.science/api/pith-number/ELVRHMGEPUC63ZX75A3XHQMIQ4/graph.json","fetch_events":"https://pith.science/api/pith-number/ELVRHMGEPUC63ZX75A3XHQMIQ4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4/action/storage_attestation","attest_author":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4/action/author_attestation","sign_citation":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4/action/citation_signature","submit_replication":"https://pith.science/pith/ELVRHMGEPUC63ZX75A3XHQMIQ4/action/replication_record"}},"created_at":"2026-07-09T01:19:38.172433+00:00","updated_at":"2026-07-09T01:19:38.172433+00:00"}