Author

Hai Hu

City University of Hong Kong

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#artificial intelligence Preprint Oct 2026

A Systematic Analysis of the Predictive Power of LM Surprisal in Reading Chinese

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...

Hon-Gao Zhu, Mu-Di Xu, Yikang Liu et al. · 0 citations

Jul 2026

The First ChineseBabyLM Challenge: training data-efficient and cognitively plausible language models for Chinese

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.

Siyuan Song, Zhiheng Qian, Yun-Hao Zhang et al. · arXiv.org · 0 citations