How Much Do LLMs Know About Chinese Zero Pronouns?
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Abstract (arXiv)
Zero Pronouns (ZPs) are a pervasive linguistic phenomenon in pro-drop languages such as Chinese and have long posed a challenge for natural language processing systems. Although Large Language Models (LLMs) perform well on many Chinese language tasks, their ability to process ZPs remains poorly understood. We conduct a systematic investigation of LLMs' handling of Chinese ZPs through a sequence of linguistically motivated tasks, including identification, referentiality classification, referential type classification, resolution, and translation. A diverse set of LLMs is evaluated across all tasks. Our results show that Chinese ZPs remain highly challenging for current LLMs, particularly for upstream tasks such as identification and referentiality classification. Performance on downstream tasks, such as ZP translation, is also consistently low: even state-of-the-art reasoning-oriented LLMs correctly translate fewer than half of Chinese ZPs into English.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 31 references that are in the map. First posted on arXiv 29 May 2026.
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References · 12
- 2024Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMscited by 224
- 2023GPTEval: A Survey on Assessments of ChatGPT and GPT-4cited by 73
- 2025Large Language Models Pass the Turing Testcited by 48
- 2023Are Large Language Models Robust Coreference Resolvers?cited by 15
- 2018Translating Pro-Drop Languages with Reconstruction Modelscited by 14
- 2019One Model to Learn Both: Zero Pronoun Prediction and Translationcited by 14
- 2023A Survey on Zero Pronoun Translationcited by 9
- 2018Deep Reinforcement Learning for Chinese Zero pronoun Resolutioncited by 5
- 2016Neural Recovery Machine for Chinese Dropped Pronouncited by 4
- 2021Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolutioncited by 4
- 2023A Survey on Semantic Processing Techniquescited by 4
- 2024Evaluating the Translation Performance of Large Language Models Based on Euas-20cited by 2
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- 2024Measuring Taiwanese Mandarin Language Understanding
- 2023An Empirical Study of Instruction-tuning Large Language Models in Chinese
- 2026Reasoning or Memorization: Can LLMs Understand and Generate Chinese Xiehouyu Riddles?