activity
20222025
most citedmPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

168 citations · 351 across the 19 of their papers we have counts for

collaborators

19 papers

cs.CV2025

Seeing Straight: Document Orientation Detection for Efficient OCR

Suranjan Goswami, Abhinav Ravi, Raja Kolla +5

Despite significant advances in document understanding, determining the correct orientation of scanned or photographed documents remains a critical pre-processing step in the real…

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.LG2023

TiMix: Text-aware Image Mixing for Effective Vision-Language Pre-training

Chaoya Jiang, Wei ye, Haiyang Xu +4

Self-supervised Multi-modal Contrastive Learning (SMCL) remarkably advances modern Vision-Language Pre-training (VLP) models by aligning visual and linguistic modalities. Due to no…

cs.CV2023★ 6 cited

Hallucination Augmented Contrastive Learning for Multimodal Large Language Model

Chaoya Jiang, Haiyang Xu, Mengfan Dong +7

Multi-modal large language models (MLLMs) have been shown to efficiently integrate natural language with visual information to handle multi-modal tasks. However, MLLMs still face a…

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…

cs.MM2023★ 1 cited

mPLUG-PaperOwl: Scientific Diagram Analysis with the Multimodal Large Language Model

Anwen Hu, Yaya Shi, Haiyang Xu +7

Recently, the strong text creation ability of Large Language Models(LLMs) has given rise to many tools for assisting paper reading or even writing. However, the weak diagram analys…

cs.CV2023★ 5 cited

UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model

Jiabo Ye, Anwen Hu, Haiyang Xu +11

Text is ubiquitous in our visual world, conveying crucial information, such as in documents, websites, and everyday photographs. In this work, we propose UReader, a first explorati…

cs.LG2023★ 26 cited

Evaluation and Analysis of Hallucination in Large Vision-Language Models

Junyang Wang, Yiyang Zhou, Guohai Xu +9

Large Vision-Language Models (LVLMs) have recently achieved remarkable success. However, LVLMs are still plagued by the hallucination problem, which limits the practicality in many…

cs.MM2023★ 1 cited

COPA: Efficient Vision-Language Pre-training Through Collaborative Object- and Patch-Text Alignment

Chaoya Jiang, Haiyang Xu, Wei Ye +7

Vision-Language Pre-training (VLP) methods based on object detection enjoy the rich knowledge of fine-grained object-text alignment but at the cost of computationally expensive inf…

cs.CL2023★ 17 cited

mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding

Jiabo Ye, Anwen Hu, Haiyang Xu +10

Document understanding refers to automatically extract, analyze and comprehend information from various types of digital documents, such as a web page. Existing Multi-model Large L…

cs.CV2023★ 1 cited

BUS:Efficient and Effective Vision-language Pre-training with Bottom-Up Patch Summarization

Chaoya Jiang, Haiyang Xu, Wei Ye +7

Vision Transformer (ViT) based Vision-Language Pre-training (VLP) models have demonstrated impressive performance in various tasks. However, the lengthy visual token sequences fed…

cs.CV2023★ 4 cited

Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Dataset for Pre-training and Benchmarks

Haiyang Xu, Qinghao Ye, Xuan Wu +13

To promote the development of Vision-Language Pre-training (VLP) and multimodal Large Language Model (LLM) in the Chinese community, we firstly release the largest public Chinese h…

cs.CL2023★ 3 cited

ChatPLUG: Open-Domain Generative Dialogue System with Internet-Augmented Instruction Tuning for Digital Human

Junfeng Tian, Hehong Chen, Guohai Xu +14

In this paper, we present ChatPLUG, a Chinese open-domain dialogue system for digital human applications that instruction finetunes on a wide range of dialogue tasks in a unified i…

cs.CV2023★ 28 cited

Transforming Visual Scene Graphs to Image Captions

Xu Yang, Jiawei Peng, Zihua Wang +7

We propose to Transform Scene Graphs (TSG) into more descriptive captions. In TSG, we apply multi-head attention (MHA) to design the Graph Neural Network (GNN) for embedding scene…

cs.CL2023★ 168 cited

mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Qinghao Ye, Haiyang Xu, Guohai Xu +15

Large language models (LLMs) have demonstrated impressive zero-shot abilities on a variety of open-ended tasks, while recent research has also explored the use of LLMs for multi-mo…

cs.CV2023★ 50 cited

mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

Haiyang Xu, Qinghao Ye, Ming Yan +12

Recent years have witnessed a big convergence of language, vision, and multi-modal pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized design for…

cs.CV2023★ 2 cited

Learning Trajectory-Word Alignments for Video-Language Tasks

Xu Yang, Zhangzikang Li, Haiyang Xu +7

In a video, an object usually appears as the trajectory, i.e., it spans over a few spatial but longer temporal patches, that contains abundant spatiotemporal contexts. However, mod…

cs.CV2022★ 10 cited

HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training

Qinghao Ye, Guohai Xu, Ming Yan +4

Video-language pre-training has advanced the performance of various downstream video-language tasks. However, most previous methods directly inherit or adapt typical image-language…