3 papers
cs.LG2026
A Survey of Continual Reinforcement Learning
Chaofan Pan, Xin Yang, Yanhua Li +4
Reinforcement Learning (RL) is an important machine learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in this field…
cs.AI2025
Constrained Language Model Policy Optimization via Risk-aware Stepwise Alignment
Lijun Zhang, Lin Li, Wei Wei +5
When fine-tuning pre-trained Language Models (LMs) to exhibit desired behaviors, maintaining control over risk is critical for ensuring both safety and trustworthiness. Most existi…
cs.LG2025
Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies
Yi Ma, Hongyao Tang, Chenjun Xiao +4
In recent years, the expansion of neural network models and training data has driven remarkable progress in deep learning, particularly in computer vision and natural language proc…