opendilab/awesome-diffusion-model-in-rl
A curated list of Diffusion Model in RL resources (continually updated)
Organizes diffusion model research in RL across multiple dimensions—trajectory planning, offline policy learning, and imitation learning—with papers categorized by venue and application domain (robotics, navigation, game environments). Covers both foundational approaches (iterative trajectory refinement via diffusion processes) and emerging techniques like flow matching and world models. Includes curated codebases and links implementation resources across frameworks targeting D4RL benchmarks, robotic manipulation platforms, and language-conditioned learning environments.
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