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20242026
most citedEVA: An Embodied World Model for Future Video Anticipation

1 citations · 4 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.RO2026

IOI: Decoupling Kinematics and Physics for Interactive World Models

Chengyu Bai, Peidong Jia, Tiecheng Guo +11

Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics. Interactive world models add…

cs.RO2026

MV-WAM: Manifold-Aware World Action Model with Value Augmentation

Jintao Chen, Peidong Jia, Qingpo Wuwu +13

Achieving robust and generalizable manipulation across diverse environments remains a fundamental challenge in embodied robotics. Recent world action models achieve strong in-domai…

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

VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models

Hao Wang, Xiaobao Wei, Jingyang He +10

Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominantly pretrained on 2D image d…

cs.RO2026

Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test

Chun-Kai Fan, Xiaowei Chi, Xiaozhu Ju +18

As world models gain momentum in Embodied AI, an increasing number of works explore using video foundation models as predictive world models for downstream embodied tasks like 3D p…

cs.RO2025

WoW: Towards a World omniscient World model Through Embodied Interaction

Xiaowei Chi, Peidong Jia, Chun-Kai Fan +33

Humans develop an understanding of intuitive physics through active interaction with the world. This approach is in stark contrast to current video models, such as Sora, which rely…

cs.RO2025★ 1 cited

Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain

Yulin Luo, Chun-Kai Fan, Menghang Dong +19

Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems often follow a dual-system paradigm, w…