most citedInfiniteWorld: A Unified Scalable Simulation Framework for General Visual-Language Robot Interaction

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

OntoAR-HAR: Ontology-Guided Agentic RAG with Personalized Memory for Human Activity Recognition

Xiangqing Lu, Tao Zhu, Liang Yu +6

LLMs increasingly support sensor-based human activity recognition (HAR) by linking motion signals with activity semantics and physical knowledge. Retrieval-augmented generation (RA…

cs.RO2026

EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action

Hao Wang, Jiajun Wen, Jingzhi Liu +21

Vision-language-action (VLA) policies emphasize semantic understanding, whereas world-action models (WAMs) learn predictive representations of environment dynamics. Systems that ex…

cs.RO2026

RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models

Weijia Liufu, Xiaoyu Guo, Ruiyi Chen +16

Vision-Language-Action (VLA) models remain brittle in long-horizon, contact-rich manipulation because success-only imitation provides little supervision for execution drift, while…

cs.RO2026

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model

Kaidong Zhang, Jian Zhang, Rongtao Xu +20

Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often constrained by cost: billion-scal…

cs.RO2024★ 1 cited

InfiniteWorld: A Unified Scalable Simulation Framework for General Visual-Language Robot Interaction

Pengzhen Ren, Min Li, Zhen Luo +15

Realizing scaling laws in embodied AI has become a focus. However, previous work has been scattered across diverse simulation platforms, with assets and models lacking unified inte…