4 papers
In-Context Reinforcement Learning via Communicative World Models
Fernando Martinez-Lopez, Tao Li, Yingdong Lu +1
Reinforcement learning (RL) agents often struggle to generalize to new tasks and contexts without updating their parameters, mainly because their learned representations and polici…
GPU-Parallel Multi-Task Reinforcement Learning with Demonstration Guided Policy Optimization
Rui Zhang, Qiwei Wu, Zhengyu Zhang +5
Large scale GPU-parallel reinforcement learning has changed what can be trained in robot simulation, yet most systems still optimize one specialist policy per task. We propose a co…
Stackelberg Coupling of Online Representation Learning and Reinforcement Learning
Fernando Martinez, Tao Li, Yingdong Lu +1
Deep Q-learning jointly learns representations and values within monolithic networks, promising beneficial co-adaptation between features and value estimates. Although this archite…
SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Models
Mohamed Afane, Abhishek Satyam, Ke Chen +3
Backdoor attacks create significant security threats to language models by embedding hidden triggers that manipulate model behavior during inference, presenting critical risks for…