mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
#Awesome#A curated list of recent and past chart understanding work based on our IEEE TKDE survey paper: From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models...
#计算机科学#[NeurIPS 2024] CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
[ICLR2025 Oral] ChartMoE: Mixture of Diversely Aligned Expert Connector for Chart Understanding
Code and data for the ACL 2024 Findings paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning"
ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models
This is the official repository for our paper 📄 “In-Depth and In-Breadth: Pre-training Multimodal Language Models Customized for Comprehensive Chart Understanding”