168 citations · 380 across the 31 of their papers we have counts for
12 papers · 1 filter
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…
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…
ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models
Chenliang Li, Hehong Chen, Ming Yan +11
Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further u…
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…
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…
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…
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…
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…
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…
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…
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…
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…