3 papers
cs.CL2026
AWPO: Enhancing Tool-Use of Large Language Models through Adaptive Integration of Reasoning Rewards
Zihan Lin, Xiaohan Wang, Hexiong Yang +5
While Reinforcement Learning (RL) shows promise in training tool-use Large Language Models (LLMs) using verifiable outcome rewards, existing methods largely overlook the potential…
cs.CV2025
Towards Robust Defense against Customization via Protective Perturbation Resistant to Diffusion-based Purification
Wenkui Yang, Jie Cao, Junxian Duan +1
Diffusion models like Stable Diffusion have become prominent in visual synthesis tasks due to their powerful customization capabilities, which also introduce significant security r…
cs.CL2025
ResT: Reshaping Token-Level Policy Gradients for Tool-Use Large Language Models
Zihan Lin, Xiaohan Wang, Jie Cao +4
Large language models (LLMs) transcend passive generation and act as goal-directed agents by invoking external tools. Reinforcement learning (RL) offers a principled framework for…