activity
20232026
most citedGPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation

10 citations · 21 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Cracking Mobile Manipulation: From Failure Diagnosis to Agentic Robot System

Zixuan Wang, Jia-Ning Li, Yinzhou Tang +5

Recent vision-language-action (VLA) models have shown strong performance on local robot manipulation, yet their success does not readily translate to long-horizon mobile manipulati…

cs.CV2026

MARS: Systematic Multi-Level Acceleration for World Action Models

Zengyuan Zuo, Yongchang Zhang, Guangyu Zhao +4

World Action Models (WAMs) have emerged as a promising alternative for embodied intelligence by jointly predicting future world states and robot actions. However, their heavy visua…

cs.RO2026

Data Pyramid for Embodied Manipulation: A Survey

Yifan Ye, Yankai Fu, Yaoxu Lv +26

Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…

cs.CV2026

DOSE: Data Selection for Multi-Modal LLMs via Off-the-Shelf Models

Biao Wu, Yiwu Zhong, Meng Fang +1

High-quality and diverse multimodal data are essential for improving vision-language models (VLMs), yet existing datasets often contain noisy, redundant, and poorly aligned samples…

cs.CV2024★ 2 cited

TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

Mu Cai, Reuben Tan, Jianrui Zhang +12

Understanding fine-grained temporal dynamics is crucial for multimodal video comprehension and generation. Due to the lack of fine-grained temporal annotations, existing video benc…

cs.CV2023★ 10 cited

GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation

An Yan, Zhengyuan Yang, Wanrong Zhu +9

We present MM-Navigator, a GPT-4V-based agent for the smartphone graphical user interface (GUI) navigation task. MM-Navigator can interact with a smartphone screen as human users,…

cs.CV2023★ 9 cited

Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models

An Yan, Yu Wang, Yiwu Zhong +8

Medical image classification is a critical problem for healthcare, with the potential to alleviate the workload of doctors and facilitate diagnoses of patients. However, two challe…