20 citations · 29 across the 15 of their papers we have counts for
8 papers · 1 filter
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
Yuang Ai, Xiaoqiang Zhou, Huaibo Huang +4
Image restoration (IR) in real-world scenarios presents significant challenges due to the lack of high-capacity models and comprehensive datasets. To tackle these issues, we presen…
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured Data
Xuwu Wang, Qiwen Cui, Yunzhe Tao +16
Large language models (LLMs) have become increasingly pivotal across various domains, especially in handling complex data types. This includes structured data processing, as exempl…
InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
Xiaotian Han, Yiren Jian, Xuefeng Hu +8
Pre-training on large-scale, high-quality datasets is crucial for enhancing the reasoning capabilities of Large Language Models (LLMs), especially in specialized domains such as ma…
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model
Haogeng Liu, Quanzeng You, Xiaotian Han +4
In the realm of Multimodal Large Language Models (MLLMs), vision-language connector plays a crucial role to link the pre-trained vision encoders with Large Language Models (LLMs).…
ViTAR: Vision Transformer with Any Resolution
Qihang Fan, Quanzeng You, Xiaotian Han +5
This paper tackles a significant challenge faced by Vision Transformers (ViTs): their constrained scalability across different image resolutions. Typically, ViTs experience a perfo…
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Haogeng Liu, Quanzeng You, Xiaotian Han +7
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intri…
Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning
Yiqi Wang, Wentao Chen, Xiaotian Han +7
Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large…
COCO is "ALL'' You Need for Visual Instruction Fine-tuning
Xiaotian Han, Yiqi Wang, Bohan Zhai +2
Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. Visual instruction fine-tuning (IFT) is a vital process for aligning M…