Tag: Calibration-Aware Policy Optimization
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EVPO: Adaptive Policy Optimization for LLM Post-Training
Discover EVPO, an adaptive policy optimization method that improves LLM post-training by balancing critic use to reduce variance and boost performance.
M2GRPO: Multi-Agent Policy Optimization for Underwater Robots
Discover M2GRPO, a novel multi-agent policy optimization method enhancing biomimetic underwater robots' cooperative pursuit and decision-making.
Boost LLM Consistency with Group Relative Policy Optimization
Improve large language model reliability using Group Relative Policy Optimization for consistent, stable recommendations across varied prompts.
TeLAPA: Enhancing Plasticity in Continual Reinforcement Learning
Discover TeLAPA, a framework that preserves policy plasticity and boosts adaptation in continual reinforcement learning with diverse policy neighborhoods.
Overcoming Surrogate Hacking in Multi-Timescale PPO
Discover how Target Decoupling architecture improves multi-timescale PPO by preventing surrogate hacking and enhancing reinforcement learning performance.