Papers by Guangxin Li

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Challenge:	Existing studies have focused on lexical- and sentence-level simplification, leaving long text simplification comparatively unexplored .
Approach:	They propose a two-level and progressive LLM-based framework that establishes an effective paradigm for automatic long text simplification under diverse test scenarios.
Outcome:	The proposed framework outperforms advanced and proprietary LLMs in in-domain and out-of-domain simplification tasks and matches or outperformed existing LLM frameworks.