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A Systematic Assessment of Language Models with Linguistic Minimal Pairs in Chinese

arXiv — cs.CL•Tuesday, December 9, 2025 at 5:00:00 AM
NeutralArtificial Intelligence
  • A systematic assessment has been conducted on Chinese language models (LMs) using the ZhoBLiMP benchmark, which includes over 100 linguistic minimal pairs. The study reveals that LMs struggle with certain linguistic constructs in Chinese, such as anaphors and quantifiers, even with models up to 32 billion parameters. A new metric, sub
  • This development is significant as it highlights the limitations of current LMs in understanding complex linguistic structures in Chinese, indicating a need for improved evaluation methods. The introduction of SLLN
  • The findings resonate with ongoing discussions in the field of AI regarding the effectiveness of large language models across different languages. Similar studies have shown that LMs can differentiate grammatical structures in various languages, suggesting a broader challenge in developing models that can universally handle linguistic nuances. This underscores the importance of tailored benchmarks and metrics in advancing AI language understanding.
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