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Yan Huang

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Preprint Oct 2026

ViDAL: A Visual Dynamics-Grounded Action Latent Space for Vision-Language-Action Models

Vision-Language-Action (VLA) models have become a central paradigm for robot policy learning, which predict actions in three forms: raw action chunks, discrete action tokens, or continuous action latents. However, existing action representations primarily model action trajectories, with limited consideration of the vis...

Yuan Xu, Yi-Xiang Chen, Qi-Sen Ma et al. · 0 citations
Preprint Sep 2026

From World Models to World Action Models: Rethinking Next-State Prediction

CF-WAM is proposed, a dynamic next-state prediction framework that samples visual, semantic, geometric, and interaction projections of the same future, standardizes them into a common video form, and supervises a unified WAM across these projections.

Ting-Yu Yuan, Zi-Ming Ji, Biao-Liang Guan et al. · 1 citation
#artificial intelligence Preprint Sep 2026

OPIS: An Input-Grounded Benchmark for Multi-Object Memory in Video World Models

OPIS is introduced, an input-grounded benchmark that strictly anchors the assessment to a fixed set of object instances from the initial observation for evaluating multi-object memory in video world models and demonstrates that preserving the particular object instances in the input is considerably harder than generati...

Hao Wang, Tao Yu, Liu-Zhou Zhang et al. · 0 citations
Preprint Aug 2026

BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation

BridgeVLA++ is developed by equipping BridgeVLA with a unified spatio-temporal memory architecture that models persistent spatial context and temporal interaction history that can reason over observation histories while preserving BridgeVLA's data efficiency and generalization capabilities.

Pei-Yan Li, Yuze Zhu, Yixiang Chen et al. · 2 citations · ⚡1
Jul 2026

Style over Substance: A Shortcut Audit of Emotion-Description Preference Evaluation

A systematic shortcut audit of EmoPrefer using content-blind probes shows that the current scores can be reached without verifying either description against the video, and recommends source-balanced pairing, strict length control, counter-stereotypical sliced reporting, and multi-annotator consensus for future cross-g...

Jia-Bing Yang, Yixiang Chen, Yuan Xu et al. · 0 citations
Preprint Aug 2026

XEWorld: Can Action-Conditioned World Models Generalize to Unseen Robot Embodiments?

XEWorld is introduced, a controlled cross-embodiment testbed for world models that isolates embodiments by evaluating held-out robots within physically identical scenes, highlighting that achieving true cross-embodiment generalization requires architectural innovations that decouple visual appearance from underlying ph...

Yixiang Chen, Jiabing Yang, Yuan Xu et al. · 0 citations

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