Presents MT-Libero, a GPU-parallel multi-task RL benchmark in Isaac Lab, and DGPO, an on-policy method combining importance-weighted PPO with adaptive behavior cloning from demonstrations.
Demonstrating gpu parallelized robot simulation and rendering for generalizable embodied ai with ManiSkill3,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2representative citing papers
Survey organizing world models for robotic manipulation into representation families, a functional taxonomy, and infrastructure roles across pretraining, post-training, and inference, while reviewing 34 datasets and evaluation protocols.
citing papers explorer
-
GPU-Parallel Multi-Task Reinforcement Learning with Demonstration Guided Policy Optimization
Presents MT-Libero, a GPU-parallel multi-task RL benchmark in Isaac Lab, and DGPO, an on-policy method combining importance-weighted PPO with adaptive behavior cloning from demonstrations.
-
World Models for Robotic Manipulation: A Survey
Survey organizing world models for robotic manipulation into representation families, a functional taxonomy, and infrastructure roles across pretraining, post-training, and inference, while reviewing 34 datasets and evaluation protocols.