54 citations · 83 across the 8 of their papers we have counts for
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cs.CL2025
ConfTuner: Training Large Language Models to Express Their Confidence Verbally
Yibo Li, Miao Xiong, Jiaying Wu +1
Large Language Models (LLMs) are increasingly deployed in high-stakes domains such as science, law, and healthcare, where accurate expressions of uncertainty are essential for reli…
cs.CL2023★ 23 cited
Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection
Jiaying Wu, Shen Li, Ailin Deng +2
Despite considerable advances in automated fake news detection, due to the timely nature of news, it remains a critical open question how to effectively predict the veracity of new…
cs.CL2023★ 54 cited
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu +4
Empowering large language models to accurately express confidence in their answers is essential for trustworthy decision-making. Previous confidence elicitation methods, which prim…