{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5J47NIT446DPR3RM4KZLPVQ5FT","short_pith_number":"pith:5J47NIT4","schema_version":"1.0","canonical_sha256":"ea79f6a27ce786f8ee2ce2b2b7d61d2cfbcdf522d80a1712bc44bd5bc3527ac0","source":{"kind":"arxiv","id":"2503.00995","version":1},"attestation_state":"computed","paper":{"title":"Evaluating Polish linguistic and cultural competency in large language models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ma{\\l}gorzata Gr\\k{e}bowiec, Micha{\\l} Pere{\\l}kiewicz, Rafa{\\l} Po\\'swiata, S{\\l}awomir Dadas","submitted_at":"2025-03-02T19:27:10Z","abstract_excerpt":"Large language models (LLMs) are becoming increasingly proficient in processing and generating multilingual texts, which allows them to address real-world problems more effectively. However, language understanding is a far more complex issue that goes beyond simple text analysis. It requires familiarity with cultural context, including references to everyday life, historical events, traditions, folklore, literature, and pop culture. A lack of such knowledge can lead to misinterpretations and subtle, hard-to-detect errors. To examine language models' knowledge of the Polish cultural context, we"},"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":"2503.00995","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-03-02T19:27:10Z","cross_cats_sorted":[],"title_canon_sha256":"393ec47533437d2afe79d1514610271ed8655b233d23dfc6939de87e3203bb79","abstract_canon_sha256":"a532c3696066e0fdc1922ce51f94c9d35cf32aba972e06f87e43c3889729ec4c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:22:34.202496Z","signature_b64":"BAItRqDwimWbTINQWlp8FgPM3Sg7m99QEXmL1xZFSWoy+hhrY/WsGLzyEBGJR0D2OeddEKdY9pIRN25a/LyhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea79f6a27ce786f8ee2ce2b2b7d61d2cfbcdf522d80a1712bc44bd5bc3527ac0","last_reissued_at":"2026-07-05T10:22:34.202012Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:22:34.202012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Evaluating Polish linguistic and cultural competency in large language models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ma{\\l}gorzata Gr\\k{e}bowiec, Micha{\\l} Pere{\\l}kiewicz, Rafa{\\l} Po\\'swiata, S{\\l}awomir Dadas","submitted_at":"2025-03-02T19:27:10Z","abstract_excerpt":"Large language models (LLMs) are becoming increasingly proficient in processing and generating multilingual texts, which allows them to address real-world problems more effectively. However, language understanding is a far more complex issue that goes beyond simple text analysis. It requires familiarity with cultural context, including references to everyday life, historical events, traditions, folklore, literature, and pop culture. A lack of such knowledge can lead to misinterpretations and subtle, hard-to-detect errors. To examine language models' knowledge of the Polish cultural context, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.00995","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/2503.00995/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":"2503.00995","created_at":"2026-07-05T10:22:34.202065+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.00995v1","created_at":"2026-07-05T10:22:34.202065+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.00995","created_at":"2026-07-05T10:22:34.202065+00:00"},{"alias_kind":"pith_short_12","alias_value":"5J47NIT446DP","created_at":"2026-07-05T10:22:34.202065+00:00"},{"alias_kind":"pith_short_16","alias_value":"5J47NIT446DPR3RM","created_at":"2026-07-05T10:22:34.202065+00:00"},{"alias_kind":"pith_short_8","alias_value":"5J47NIT4","created_at":"2026-07-05T10:22:34.202065+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2608.07763","citing_title":"Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation","ref_index":4,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT","json":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT.json","graph_json":"https://pith.science/api/pith-number/5J47NIT446DPR3RM4KZLPVQ5FT/graph.json","events_json":"https://pith.science/api/pith-number/5J47NIT446DPR3RM4KZLPVQ5FT/events.json","paper":"https://pith.science/paper/5J47NIT4"},"agent_actions":{"view_html":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT","download_json":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT.json","view_paper":"https://pith.science/paper/5J47NIT4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.00995&json=true","fetch_graph":"https://pith.science/api/pith-number/5J47NIT446DPR3RM4KZLPVQ5FT/graph.json","fetch_events":"https://pith.science/api/pith-number/5J47NIT446DPR3RM4KZLPVQ5FT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT/action/storage_attestation","attest_author":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT/action/author_attestation","sign_citation":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT/action/citation_signature","submit_replication":"https://pith.science/pith/5J47NIT446DPR3RM4KZLPVQ5FT/action/replication_record"}},"created_at":"2026-07-05T10:22:34.202065+00:00","updated_at":"2026-07-05T10:22:34.202065+00:00"}