activity
20242026
most citedWan: Open and Advanced Large-Scale Video Generative Models

12 citations · 30 across the 17 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.AI2025

DeliveryBench: Can Agents Earn Profit in Real World?

Lingjun Mao, Jiawei Ren, Kun Zhou +3

LLMs and VLMs are increasingly deployed as embodied agents, yet existing benchmarks largely revolve around simple short-term tasks and struggle to capture rich realistic constraint…

cs.CL2025

VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos

Dunjie Lu, Yiheng Xu, Junli Wang +12

Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgen…

cs.AI2025

OpenCUA: Open Foundations for Computer-Use Agents

Xinyuan Wang, Bowen Wang, Dunjie Lu +39

Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, cr…

cs.CV2025★ 1 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…

cs.AI2025

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems

Xiaozhe Li, Jixuan Chen, Xinyu Fang +4

Large Language Models (LLMs) have shown remarkable capabilities in solving diverse tasks. However, their proficiency in iteratively optimizing complex solutions through learning fr…

cs.AI2025

Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis

Tianbao Xie, Jiaqi Deng, Xiaochuan Li +12

Graphical user interface (GUI) grounding, the ability to map natural language instructions to specific actions on graphical user interfaces, remains a critical bottleneck in comput…

cs.CV2025★ 12 cited

Wan: Open and Advanced Large-Scale Video Generative Models

Team Wan, Ang Wang, Baole Ai +58

This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transfo…

cs.CV2025

CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness

Zhihang Liu, Chen-Wei Xie, Bin Wen +9

Visual captioning benchmarks have become outdated with the emergence of modern multimodal large language models (MLLMs), as the brief ground-truth sentences and traditional metrics…