5 papers
Controllable Concept Bottleneck Models
Hongbin Lin, Chenyang Ren, Juangui Xu +7
Concept Bottleneck Models (CBMs) have garnered much attention for their ability to elucidate the prediction process through a human-understandable concept layer. However, most prev…
Towards Acyclic Preference Evaluation of Language Models via Multiple Evaluators
Zhengyu Hu, Jieyu Zhang, Zhihan Xiong +3
Despite the remarkable success of Large Language Models (LLMs), evaluating their outputs' quality regarding preference remains a critical challenge. While existing works usually le…
Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao +5
Large language models (LLMs) have shown impressive capabilities across tasks such as mathematics, coding, and reasoning, yet their learning ability, which is crucial for adapting t…
Explaining Length Bias in LLM-Based Preference Evaluations
Zhengyu Hu, Linxin Song, Jieyu Zhang +7
The use of large language models (LLMs) as judges, particularly in preference comparisons, has become widespread, but this reveals a notable bias towards longer responses, undermin…
LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System
Tianfu Wang, Yi Zhan, Jianxun Lian +5
Intelligent Tutoring Systems (ITSs) have revolutionized education by offering personalized learning experiences. However, as goal-oriented learning, which emphasizes efficiently ac…