Yuanzhao Guo — accepted AI-conference papers

2025

Detoxifying Large Language Models via the Diversity of Toxic Samples

Ying Zhao, Yuanzhao Guo, Xuemeng Weng, Yuan Tian, Wei Wang, Yi Chang

EMNLP 2025

Eliminating toxicity from Large Language Models (LLMs) is crucial for ensuring user safety. However, current methods have limitations in the analysis and utilization of toxic samples, failing to fully harness their potential. Through comparative analysis of toxic and safe samples, we discover that t

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2025

RACQC: Advanced Retrieval-Augmented Generation for Chinese Query Correction

Jinbo Su, Lingzhe Gao, Wei Li, Shihao Liu, Haojie Lei, Xinyi Wang +4

EMNLP 2025

In web search scenarios, erroneous queries frequently degrade users’ experience through irrelevant results, underscoring the pivotal role of Chinese Spelling Check (CSC) systems. Although large language models (LLMs) exhibit remarkable capabilities across many tasks, they face critical challenges in

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