Papers by Luming Li

2 papers
MCTS: A Multi-Reference Chinese Text Simplification Dataset (2024.lrec-main)

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Challenge: Existing studies on text simplification systems have focused on unsupervised methods due to the limited evaluation data in language and domain.
Approach: They propose a Chinese text simplification dataset that provides a detailed analysis and an annotation process.
Outcome: The proposed dataset evaluates the performance of unsupervised methods and advanced large language models.
CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization (2026.acl-long)

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Challenge: Existing approaches to formalizing mathematical statements face limitations in accuracy, especially in the context of complex, highlevel problems that involve sophisticated mathematical reasoning.
Approach: They propose a CriticLean framework that elevates the role of the critic from a passive validator to an active learning component and introduce a benchmark to measure models’ ability to distinguish semantically correct from incorrect formalizations.
Outcome: The proposed framework outperforms open- and closed-source benchmarks and shows that it significantly outperformed existing models.

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