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[IEEE VIS 2024] LLaVA-Chart: Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning

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Officical repository for the paper“ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering”(EMNLP'24)

Minimal code to expirement Qwen-VL 2.5 series with VQA tasks such as ChartQA

Fine-tuning Vision Language Model (Qwen2.5-VL-7B) with Hugging Face TRL - Tutorial and implementation for visual question-answering on ChartQA dataset

This is the main repository for the Misleading ChartQA project.

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Visual RAG Benchmarking on ChartQA Dataset

Vision-language AI for chart question answering using Qwen3-VL with SFT and GRPO training

This is the official repository for our paper 📄 “In-Depth and In-Breadth: Pre-training Multimodal Language Models Customized for Comprehensive Chart Understanding”

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ESAPI script which creates PDFs of chart check information and puts it in ARIA's document module so it can be transferred to EPIC

Finetune Qwen 2.5 VLM in AWS Clusters. Quantization code for AWQ also provided. Training occurs in bf16 to preserve accuracy of the model (Sample dataset is ChartQA)

Korea-ChartQA 생성 방법론

ChartQA data serving repo

qwen finetuned in chartQA dataset

Reproduce VL-T5 experiment in ChartQA

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Project page for ChartQA-X

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识别图表内容并进行回答的VLM项目

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