{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:YMCVCRRYK2L3IGD54HGZMBOY5B","short_pith_number":"pith:YMCVCRRY","schema_version":"1.0","canonical_sha256":"c3055146385697b4187de1cd9605d8e8696db7b82032a72d1cce5131b1e3d17d","source":{"kind":"arxiv","id":"2601.04693","version":2},"attestation_state":"computed","paper":{"title":"Thunder-KoNUBench: A Corpus-Aligned Benchmark for Korean Negation Understanding","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jaejin Lee, Joonhak Lee, Sangho Kim, Sungmok Jung, Yelim Ahn, Yeonkyoung So","submitted_at":"2026-01-08T08:02:52Z","abstract_excerpt":"Although negation is known to challenge large language models (LLMs), benchmarks for evaluating negation understanding-especially in Korean-are scarce. We conduct a corpus-based analysis of Korean negation and show that LLM performance degrades under negation. We then introduce Thunder-KoNUBench, a sentence-level negation understanding benchmark that reflects the empirical distribution of Korean negation phenomena. Evaluating 47 LLMs on Thunder-KoNUBench, we analyze the effects of model size and instruction tuning, and perform error analysis to better understand model behavior. We further show"},"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":"2601.04693","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-01-08T08:02:52Z","cross_cats_sorted":[],"title_canon_sha256":"ab3ca6e4443687e02eedb1d99c634e36809340a67cc86f57e09054a926d9c796","abstract_canon_sha256":"be6032d3582d8c140e42d26a9bf0d3a196efceaebe151187fc353456453ea115"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:17:32.172985Z","signature_b64":"0Nu6xeVCPZ1rFdPg4q9CPEbniizg3MDSlexFz5QTzPe4HlHJ7X3AgY/orel/Rs9NdLNWKE9HVyr4tgVH87bFDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3055146385697b4187de1cd9605d8e8696db7b82032a72d1cce5131b1e3d17d","last_reissued_at":"2026-06-30T01:17:32.172236Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:17:32.172236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Thunder-KoNUBench: A Corpus-Aligned Benchmark for Korean Negation Understanding","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jaejin Lee, Joonhak Lee, Sangho Kim, Sungmok Jung, Yelim Ahn, Yeonkyoung So","submitted_at":"2026-01-08T08:02:52Z","abstract_excerpt":"Although negation is known to challenge large language models (LLMs), benchmarks for evaluating negation understanding-especially in Korean-are scarce. We conduct a corpus-based analysis of Korean negation and show that LLM performance degrades under negation. We then introduce Thunder-KoNUBench, a sentence-level negation understanding benchmark that reflects the empirical distribution of Korean negation phenomena. Evaluating 47 LLMs on Thunder-KoNUBench, we analyze the effects of model size and instruction tuning, and perform error analysis to better understand model behavior. We further show"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.04693","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/2601.04693/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":"2601.04693","created_at":"2026-06-30T01:17:32.172337+00:00"},{"alias_kind":"arxiv_version","alias_value":"2601.04693v2","created_at":"2026-06-30T01:17:32.172337+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.04693","created_at":"2026-06-30T01:17:32.172337+00:00"},{"alias_kind":"pith_short_12","alias_value":"YMCVCRRYK2L3","created_at":"2026-06-30T01:17:32.172337+00:00"},{"alias_kind":"pith_short_16","alias_value":"YMCVCRRYK2L3IGD5","created_at":"2026-06-30T01:17:32.172337+00:00"},{"alias_kind":"pith_short_8","alias_value":"YMCVCRRY","created_at":"2026-06-30T01:17:32.172337+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/YMCVCRRYK2L3IGD54HGZMBOY5B","json":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B.json","graph_json":"https://pith.science/api/pith-number/YMCVCRRYK2L3IGD54HGZMBOY5B/graph.json","events_json":"https://pith.science/api/pith-number/YMCVCRRYK2L3IGD54HGZMBOY5B/events.json","paper":"https://pith.science/paper/YMCVCRRY"},"agent_actions":{"view_html":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B","download_json":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B.json","view_paper":"https://pith.science/paper/YMCVCRRY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2601.04693&json=true","fetch_graph":"https://pith.science/api/pith-number/YMCVCRRYK2L3IGD54HGZMBOY5B/graph.json","fetch_events":"https://pith.science/api/pith-number/YMCVCRRYK2L3IGD54HGZMBOY5B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B/action/storage_attestation","attest_author":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B/action/author_attestation","sign_citation":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B/action/citation_signature","submit_replication":"https://pith.science/pith/YMCVCRRYK2L3IGD54HGZMBOY5B/action/replication_record"}},"created_at":"2026-06-30T01:17:32.172337+00:00","updated_at":"2026-06-30T01:17:32.172337+00:00"}