Papers by Xiaoshan He

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Challenge:	Existing studies on eye movement in text quality assessment are limited . eye-movement features are important predictors of human judgments of text quality, but are costly and inconsistent.
Approach:	They propose to capture eye-movement features during screen reading of LLM-generated text using a dataset that includes eye-motion recordings, reading-time measurements, and post-reading evaluations.
Outcome:	The proposed dataset shows that eye-movement features can significantly improve models over other probabilistic metrics, including negative log-likelihood (NLL).