Tag: adversarial reinforcement learning
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Efficient Diffusion RL with FP4 Quantization & Sol-RL
Discover Sol-RL: a two-stage FP4 and BF16 framework boosting diffusion RL efficiency and training speed by 4.64× for text-to-image models.
TwinLoop: Digital Twins Boost Multi-Agent Reinforcement Learning
Discover how TwinLoop uses simulation-in-the-loop digital twins to enhance online multi-agent reinforcement learning and speed up adaptation.
Discrete Flow Matching Policy Optimization for RL Models
Discover DoMinO, a novel RL framework optimizing discrete flow matching with robust policy gradients and improved sequence generation.
T-STAR: Tree-Based Policy Optimization for Multi-Turn Agents
Discover T-STAR, a novel tree-structured framework enhancing multi-turn agent policy optimization through self-rectification and grafting techniques.
KD-MARL: Efficient Knowledge Distillation for Multi-Agent RL
KD-MARL enables resource-aware knowledge distillation in multi-agent reinforcement learning, reducing compute costs while preserving expert coordination an...