9 citations · 26 across the 15 of their papers we have counts for
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cs.CL2024★ 5 cited
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection
Pei Wang, Keqing He, Yejie Wang +6
Out-of-domain (OOD) intent detection aims to examine whether the user's query falls outside the predefined domain of the system, which is crucial for the proper functioning of task…
cs.CL2024
Multi-Perspective Consistency Enhances Confidence Estimation in Large Language Models
Pei Wang, Yejie Wang, Muxi Diao +3
In the deployment of large language models (LLMs), accurate confidence estimation is critical for assessing the credibility of model predictions. However, existing methods often fa…
cs.CL2024
DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning
Yejie Wang, Keqing He, Guanting Dong +8
Code Large Language Models (Code LLMs) have demonstrated outstanding performance in code-related tasks. Several instruction tuning approaches have been proposed to boost the code g…