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cs.RO2026

Fast-dVLA: Accelerating Discrete Diffusion VLA to Real-Time Performance

Wenxuan Song, Jiayi Chen, Shuai Chen +8

This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adaptation costs during standard s…

cs.RO2026

Rethinking the Practicality of Vision-language-action Model: A Comprehensive Benchmark and An Improved Baseline

Wenxuan Song, Jiayi Chen, Xiaoquan Sun +12

Vision-Language-Action (VLA) models have emerged as a generalist robotic agent. However, existing VLAs are hindered by excessive parameter scales, prohibitive pre-training requirem…

cs.RO2025

Unified Diffusion VLA: Vision-Language-Action Model via Joint Discrete Denoising Diffusion Process

Jiayi Chen, Wenxuan Song, Pengxiang Ding +5

Vision-language-action (VLA) models aim to understand natural language instructions and visual observations and to execute corresponding actions as an embodied agent. Recent work i…

cs.RO2025

ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver

Wenxuan Song, Ziyang Zhou, Han Zhao +7

Recent advances in Vision-Language-Action (VLA) models have enabled robotic agents to integrate multimodal understanding with action execution. However, our empirical analysis reve…

cs.RO2025

FlowVLA: Visual Chain of Thought-based Motion Reasoning for Vision-Language-Action Models

Zhide Zhong, Haodong Yan, Junfeng Li +8

Many Vision-Language-Action (VLA) models are built upon an internal world model trained via next-frame prediction ``''. However, this paradigm attempts to…

cs.RO2025

CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit Decoding

Wenxuan Song, Jiayi Chen, Pengxiang Ding +4

In recent years, Vision-Language-Action (VLA) models have become a vital research direction in robotics due to their impressive multimodal understanding and generalization capabili…