activity
20232026
most citedmPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

29 citations · 39 across the 8 of their papers we have counts for

collaborators

10 papers

cs.AI2026

HyWe: Unifying Search and Operation for Real-World Hybrid Web Tasks

Zijian Cai, Haowei Liu, Kailai Chen +7

Real-world hybrid web tasks need both information gathering and page interaction, yet search-based and operation-based agents are developed and evaluated separately. To bridge this…

cs.AI2025

Mobile-Agent-v3: Fundamental Agents for GUI Automation

Jiabo Ye, Xi Zhang, Haiyang Xu +12

This paper introduces GUI-Owl, a foundational GUI agent model that achieves state-of-the-art performance among open-source end-to-end models on ten GUI benchmarks across desktop an…

cs.AI2025

Look Before You Leap: A GUI-Critic-R1 Model for Pre-Operative Error Diagnosis in GUI Automation

Yuyang Wanyan, Xi Zhang, Haiyang Xu +9

In recent years, Multimodal Large Language Models (MLLMs) have been extensively utilized for multimodal reasoning tasks, including Graphical User Interface (GUI) automation. Unlike…

cs.CV2025

PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC

Haowei Liu, Xi Zhang, Haiyang Xu +8

In the field of MLLM-based GUI agents, compared to smartphones, the PC scenario not only features a more complex interactive environment, but also involves more intricate intra- an…

cs.CV2024★ 6 cited

mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models

Jiabo Ye, Haiyang Xu, Haowei Liu +6

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in executing instructions for a variety of single-image tasks. Despite this progress, significan…

cs.CV2024★ 1 cited

MIBench: Evaluating Multimodal Large Language Models over Multiple Images

Haowei Liu, Xi Zhang, Haiyang Xu +8

Built on the power of LLMs, numerous multimodal large language models (MLLMs) have recently achieved remarkable performance on various vision-language tasks. However, most existing…

cs.CV2024

Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training

Haowei Liu, Yaya Shi, Haiyang Xu +8

In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment. However, in most existing methods, the recon…

cs.CV2024

Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval

Haowei Liu, Yaya Shi, Haiyang Xu +8

In video-text retrieval, most existing methods adopt the dual-encoder architecture for fast retrieval, which employs two individual encoders to extract global latent representation…

cs.IR2024★ 3 cited

NFT1000: A Cross-Modal Dataset for Non-Fungible Token Retrieval

Shuxun Wang, Yunfei Lei, Ziqi Zhang +6

With the rise of "Metaverse" and "Web 3.0", Non-Fungible Token (NFT) has emerged as a kind of pivotal digital asset, garnering significant attention. By the end of March 2024, more…

cs.CL2023★ 29 cited

mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

Qinghao Ye, Haiyang Xu, Jiabo Ye +7

Multi-modal Large Language Models (MLLMs) have demonstrated impressive instruction abilities across various open-ended tasks. However, previous methods primarily focus on enhancing…