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This study analyzes the predictive power of LM-derived, token-level surprisal on Mandarin Chinese reading times. We first propose the Shortest Matching Sequence (SMS), an alignment scheme that maps between the word segmentation assumed by eye-tracking corpora and the LMs'subword tokenization, as the two tokenizations o...
The first ChineseBabyLM Challenge, organized as part of NLPCC 2026, asked participants to train language models from scratch using no more than 102M Chinese words and provides a benchmark for advancing data-efficient and cognitively plausible approaches to Chinese language modeling.
The impressive linguistic abilities of large language models (LLMs) have recommended them as models of human sentence processing, with some conjecturing a positive'quality-power'relationship, in which language models'(LMs') fit to psychometric data continues to improve as their ability to predict words in context incre...
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