64 citations · 283 across the 92 of their papers we have counts for
5 papers · 2 filters
EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus
Shouang Wei, Min Zhang, Xin Lin +3
Recently, several multi-turn dialogue benchmarks have been proposed to evaluate the conversational abilities of large language models (LLMs). As LLMs are increasingly recognized as…
Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction
Tao Wu, Jingyuan Chen, Wang Lin +6
Distractors-incorrect yet plausible answer choices in multiple-choice questions (MCQs)-are vital in educational assessments, as they help identify student misconceptions by present…
Evaluating Test-Time Scaling LLMs for Legal Reasoning: OpenAI o1, DeepSeek-R1, and Beyond
Yinghao Hu, Yaoyao Yu, Leilei Gan +3
Recent advances in test-time scaling of large language models (LLMs), exemplified by DeepSeek-R1 and OpenAI's o1, show that extending the chain of thought during inference can sign…
Rewrite to Jailbreak: Discover Learnable and Transferable Implicit Harmfulness Instruction
Yuting Huang, Chengyuan Liu, Yifeng Feng +4
As Large Language Models (LLMs) are widely applied in various domains, the safety of LLMs is increasingly attracting attention to avoid their powerful capabilities being misused. E…
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
Yinghao Hu, Leilei Gan, Wenyi Xiao +2
Hallucination, or the generation of incorrect or fabricated information, remains a critical challenge in large language models (LLMs), particularly in high-stake domains such as le…