Unlike English, which uses distinct forms (e.g., had, has, will have) to mark the perfect aspect across tenses, Chinese and Japanese lack sep- arate grammatical forms for tense within the perfect aspect, which complicates Natural Lan- guage Inference (NLI). Focusing on the per- fect aspect in these languages, we construct a linguistically motivated, template-based NLI dataset (1,350 pairs per language). Experi- ments reveal that even advanced LLMs strug- gle with temporal inference, particularly in de- tecting subtle tense and reference-time shifts. These findings highlight model limitations and underscore the need for cross-linguistic evalua- tion in temporal semantics. Our dataset is avail- able at https://github.com/Lujie2001/ CrossNLI.