✨✨Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
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Updated
May 11, 2024
✨✨Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
[CVPR'24] HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
Curated papers on Large Language Models in Healthcare and Medical domain
This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"
A curated list of recent and past chart understanding work based on our survey paper: From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models.
Talk2BEV: Language-Enhanced Bird's Eye View Maps (Accepted to ICRA'24)
🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
An benchmark for evaluating the capabilities of large vision-language models (LVLMs)
Code and data for the paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning"
[ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering
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