3 papers
cs.LG2025
Achieve Performatively Optimal Policy for Performative Reinforcement Learning
Ziyi Chen, Heng Huang
Performative reinforcement learning is an emerging dynamical decision making framework, which extends reinforcement learning to the common applications where the agent's policy can…
cs.CL2025
Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
Tong Zheng, Hongming Zhang, Wenhao Yu +7
Parallel thinking has emerged as a novel approach for enhancing the reasoning capabilities of large language models (LLMs) by exploring multiple reasoning paths concurrently. Howev…
cs.CR2025
Web Intellectual Property at Risk: Preventing Unauthorized Real-Time Retrieval by Large Language Models
Yisheng Zhong, Yizhu Wen, Junfeng Guo +4
The protection of cyber Intellectual Property (IP) such as web content is an increasingly critical concern. The rise of large language models (LLMs) with online retrieval capabilit…