activity
20242026
most citedLAC-Net: Linear-Fusion Attention-Guided Convolutional Network for Accurate Robotic Grasping Under the Occlusion

1 citations · 1 across the 8 of their papers we have counts for

collaborators
Showing cs.ROShow all

7 papers · 1 filter

cs.RO2026

-VLA: a Hierarchical Robot Foundation Model with World-Model-Guided Test-Time Computation

Xiaowei Cai, Yunuo Cai, Bingao Chen +36

Long-horizon robot manipulation requires a robot to both execute individual skills reliably and sequence them coherently over extended tasks. Most hierarchical vision-language-acti…

cs.RO2026

OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform

Jinyuan Zhang, Luoyi Fan, Leiyu Wang +4

Embodied AI in the real world requires both accurate hardware and robust vision-language-action (VLA) policies. We present OpenEAI-Platform, a fully open-source platform that integ…

cs.RO2026

FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies

Xintong Hu, Xuhong Huang, Jinyu Zhang +11

Vision-Language-Action (VLA) models are increasingly expected to not only complete robot tasks, but also follow human instructions about how those tasks should be executed. However…

cs.RO2026

ST4VLA: Spatially Guided Training for Vision-Language-Action Models

Jinhui Ye, Fangjing Wang, Ning Gao +9

Large vision-language models (VLMs) excel at multimodal understanding but fall short when extended to embodied tasks, where instructions must be transformed into low-level motor ac…

cs.RO2025

Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training

Yi Liu, Sukai Wang, Dafeng Wei +10

General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action execution, a combination that remains challeng…

cs.RO2025

InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy

Xinyi Chen, Yilun Chen, Yanwei Fu +26

We introduce InternVLA-M1, a unified framework for spatial grounding and robot control that advances instruction-following robots toward scalable, general-purpose intelligence. Its…