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20242026
most citedA Self-Correcting Vision-Language-Action Model for Fast and Slow System Manipulation

2 citations · 2 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.RO2026

Do Robotic World Models Really Follow Actions? Diagnosing and Aligning Action-Conditioned Generation for Policy Learning

Sixiang Chen, Jiaming Liu, Jixian Wu +11

Action-conditioned world models increasingly serve as learned simulators for robotic policy improvement, yet their reliability rests on an unverified assumption: generated futures…

cs.RO2026

Robo-Dopamine 2.0: History-Conditioned and OOD-Aware Process Reward Modeling for Robotic Manipulation

Yijie Xu, Haopeng Jin, Run Zhou +8

Vision-language-action (VLA) models improve robotic manipulation but remain vulnerable to compounding errors, scene changes, and off-trajectory states. Reinforcement learning can r…

cs.RO2026

WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation

Peterson Co, Sicheng Hu, Chunxuan Jiao +17

Action-conditioned world models (ACWMs) promise to provide embodied AI with scalable predictive simulators for planning, policy evaluation, and data generation. Realizing this prom…

cs.RO2026

SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model

Kai Tang, Peidong Jia, Zhong Chu +16

Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However, existing safe reinforcement…

cs.RO2026

RoboBrain 2.5: Depth in Sight, Time in Mind

Huajie Tan, Enshen Zhou, Zhiyu Li +32

We introduce RoboBrain 2.5, a next-generation embodied AI foundation model that advances general perception, spatial reasoning, and temporal modeling through extensive training on…

cs.RO2025

Robo-Dopamine: General Process Reward Modeling for High-Precision Robotic Manipulation

Huajie Tan, Sixiang Chen, Yijie Xu +12

The primary obstacle for applying reinforcement learning (RL) to real-world robotics is the design of effective reward functions. While recently learning-based Process Reward Model…

cs.RO2025

AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation

Sixiang Chen, Jiaming Liu, Siyuan Qian +9

Recently, mobile manipulation has attracted increasing attention for enabling language-conditioned robotic control in household tasks. However, existing methods still face challeng…