most citedInternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

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

collaborators

5 papers

cs.MA2026

OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent

Bowen Yang, Kaiming Jin, Zhenyu Wu +12

While Vision-Language Models (VLMs) have significantly advanced Computer-Using Agents (CUAs), current frameworks struggle with robustness in long-horizon workflows and generalizati…

cs.AI2025

OS-Oracle: A Comprehensive Framework for Cross-Platform GUI Critic Models

Zhenyu Wu, Jingjing Xie, Zehao Li +8

With VLM-powered computer-using agents (CUAs) becoming increasingly capable at graphical user interface (GUI) navigation and manipulation, reliable step-level decision-making has e…

cs.CV2025

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

Zhaoyang Liu, Jingjing Xie, Zichen Ding +27

Vision-Language Models (VLMs) have enabled computer use agents (CUAs) that operate GUIs autonomously, showing great potential, yet progress is limited by the lack of large-scale, o…

cs.CV20254 cited

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV20251 cited

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Xuehui Wang, Zhenyu Wu, JingJing Xie +25

We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms. It comprises four levels: GUI…