activity
20232025
most citedmPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

50 citations · 221 across the 40 of their papers we have counts for

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Showing 2024Show all

16 papers · 1 filter

cs.CV2024

SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization

Hongrui Jia, Chaoya Jiang, Haiyang Xu +6

As language models continue to scale, Large Language Models (LLMs) have exhibited emerging capabilities in In-Context Learning (ICL), enabling them to solve language tasks by prefi…

cs.CV2024

SimInversion: A Simple Framework for Inversion-Based Text-to-Image Editing

Qi Qian, Haiyang Xu, Ming Yan +1

Diffusion models demonstrate impressive image generation performance with text guidance. Inspired by the learning process of diffusion, existing images can be edited according to t…

cs.CV2024★ 1 cited

mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding

Anwen Hu, Haiyang Xu, Liang Zhang +6

Multimodel Large Language Models(MLLMs) have achieved promising OCR-free Document Understanding performance by increasing the supported resolution of document images. However, this…

cs.CL2024

MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model

Chaoya Jiang, Jia Hongrui, Haiyang Xu +6

This paper presents MaVEn, an innovative Multi-granularity Visual Encoding framework designed to enhance the capabilities of Multimodal Large Language Models (MLLMs) in multi-image…

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.CL2024

ProFuser: Progressive Fusion of Large Language Models

Tianyuan Shi, Fanqi Wan, Canbin Huang +6

While fusing the capacities and advantages of various large language models offers a pathway to construct more powerful and versatile models, a fundamental challenge is to properly…

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★ 2 cited

TinyChart: Efficient Chart Understanding with Visual Token Merging and Program-of-Thoughts Learning

Liang Zhang, Anwen Hu, Haiyang Xu +5

Charts are important for presenting and explaining complex data relationships. Recently, multimodal large language models (MLLMs) have shown remarkable capabilities in various char…

cs.CV2024★ 1 cited

mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding

Anwen Hu, Haiyang Xu, Jiabo Ye +8

Structure information is critical for understanding the semantics of text-rich images, such as documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for…

cs.CL2024★ 4 cited

SocialBench: Sociality Evaluation of Role-Playing Conversational Agents

Hongzhan Chen, Hehong Chen, Ming Yan +8

Large language models (LLMs) have advanced the development of various AI conversational agents, including role-playing conversational agents that mimic diverse characters and human…

cs.CV2024

Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection

Wei Ye, Chaoya Jiang, Haiyang Xu +6

Vision Transformers (ViTs) have become increasingly popular in large-scale Vision and Language Pre-training (VLP) models. Although previous VLP research has demonstrated the effica…

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.AI2024

Budget-Constrained Tool Learning with Planning

Yuanhang Zheng, Peng Li, Ming Yan +3

Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, ha…

cs.AI2024★ 1 cited

Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models

Chaoya Jiang, Hongrui Jia, Wei Ye +5

Large Vision Language Models exhibit remarkable capabilities but struggle with hallucinations inconsistencies between images and their descriptions. Previous hallucination evaluati…

cs.CL2024★ 13 cited

Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception

Junyang Wang, Haiyang Xu, Jiabo Ye +5

Mobile device agent based on Multimodal Large Language Models (MLLM) is becoming a popular application. In this paper, we introduce Mobile-Agent, an autonomous multi-modal mobile d…