{"ID":2881603,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.11927","arxiv_id":"2508.11927","title":"LLMs Struggle with NLI for Perfect Aspect: A Cross-Linguistic Study in Chinese and Japanese","abstract":"Unlike English, which uses distinct forms (e.g., had, has, will have) to mark the perfect aspect across tenses, Chinese and Japanese lack separate grammatical forms for tense within the perfect aspect, which complicates Natural Language Inference (NLI). Focusing on the perfect aspect in these languages, we construct a linguistically motivated, template-based NLI dataset (1,350 pairs per language). Experiments reveal that even advanced LLMs struggle with temporal inference, particularly in detecting subtle tense and reference-time shifts. These findings highlight model limitations and underscore the need for cross-linguistic evaluation in temporal semantics. Our dataset is available at https://github.com/Lujie2001/CrossNLI.","short_abstract":"Unlike English, which uses distinct forms (e.g., had, has, will have) to mark the perfect aspect across tenses, Chinese and Japanese lack separate grammatical forms for tense within the perfect aspect, which complicates Natural Language Inference (NLI). Focusing on the perfect aspect in these languages, we construct a...","url_abs":"https://arxiv.org/abs/2508.11927","url_pdf":"https://arxiv.org/pdf/2508.11927v1","authors":"[\"Jie Lu\",\"Du Jin\",\"Hitomi Yanaka\"]","published":"2025-08-16T06:16:56Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[\"Large Language Model\"]","has_code":false,"code_links":[{"ID":610829,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2881603,"paper_url":"https://arxiv.org/abs/2508.11927","paper_title":"LLMs Struggle with NLI for Perfect Aspect: A Cross-Linguistic Study in Chinese and Japanese","repo_url":"https://github.com/Lujie2001/CrossNLI","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}