most citedAIC MLLM: Autonomous Interactive Correction MLLM for Robust Robotic Manipulation

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

collaborators

5 papers

cs.RO2025

SR3D: Unleashing Single-view 3D Reconstruction for Transparent and Specular Object Grasping

Mingxu Zhang, Xiaoqi Li, Jiahui Xu +5

Recent advancements in 3D robotic manipulation have improved grasping of everyday objects, but transparent and specular materials remain challenging due to depth sensing limitation…

cs.RO2025

BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation

Hongyu Wang, Chuyan Xiong, Ruiping Wang +1

Deploying powerful Vision-Language-Action (VLA) models on edge devices is limited by their massive size. In this paper, we take a deployment-oriented view of VLA training: we targe…

cs.RO2024★ 2 cited

AIC MLLM: Autonomous Interactive Correction MLLM for Robust Robotic Manipulation

Chuyan Xiong, Chengyu Shen, Xiaoqi Li +4

The ability to reflect on and correct failures is crucial for robotic systems to interact stably with real-life objects.Observing the generalization and reasoning capabilities of M…

cs.CV2024★ 2 cited

A Self-Correcting Vision-Language-Action Model for Fast and Slow System Manipulation

Chenxuan Li, Jiaming Liu, Guanqun Wang +8

Recently, some studies have integrated Multimodal Large Language Models into robotic manipulation, constructing vision-language-action models (VLAs) to interpret multimodal informa…

cs.CV2024

M4U: Evaluating Multilingual Understanding and Reasoning for Large Multimodal Models

Hongyu Wang, Jiayu Xu, Senwei Xie +6

Multilingual capability is an essential aspect for large multimodal models, since they are usually deployed across various countries and languages. However, most existing benchmark…