5 papers
MUSIC: MUlti-Step Instruction Contrast for Multi-Turn Reward Models
Wenzhe Li, Shujian Zhang, Wenxuan Zhou +5
Evaluating the quality of multi-turn conversations is crucial for developing capable Large Language Models (LLMs), yet remains a significant challenge, often requiring costly human…
Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process
Zhenyu Zhang, Shujian Zhang, John Lambert +6
Despite the growing reasoning capabilities of recent large language models (LLMs), their internal mechanisms during the reasoning process remain underexplored. Prior approaches oft…
T-REG: Preference Optimization with Token-Level Reward Regularization
Wenxuan Zhou, Shujian Zhang, Lingxiao Zhao +1
Reinforcement learning from human feedback (RLHF) has been crucial in aligning large language models (LLMs) with human values. Traditionally, RLHF involves generating responses to…
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
Tong Wu, Shujian Zhang, Kaiqiang Song +7
Large Language Models (LLMs) are susceptible to security and safety threats, such as prompt injection, prompt extraction, and harmful requests. One major cause of these vulnerabili…
SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe
Yuxin Xiao, Shujian Zhang, Wenxuan Zhou +2
To acquire instruction-following capabilities, large language models (LLMs) undergo instruction tuning, where they are trained on instruction-response pairs using next-token predic…