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cs.RO2026
Semantically Structured Mixture-of-Experts for Compositional Robotic Manipulation
Chengyu Deng, Guanqi Chen, Yizhou Chen +4
Diffusion-based policies have established a new standard for precise robotic manipulation but face a critical scalability bottleneck: high-performance models are computationally ex…
cs.RO2026
Beyond Pixels: Learning Invariant Rewards for Real-World Robotics From a Few Demonstrations
Tengye Xu, Yangting Sun, Ziju Shen +5
Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics. In open-world manipulation…
cs.RO2024
Language-Augmented Symbolic Planner for Open-World Task Planning
Guanqi Chen, Lei Yang, Ruixing Jia +5
Enabling robotic agents to perform complex long-horizon tasks has been a long-standing goal in robotics and artificial intelligence (AI). Despite the potential shown by large langu…