Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering
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Updated
Apr 3, 2024 - Python
Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering
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up-to-date and curated list of awesome state-of-the-art LVLMs hallucinations research work, papers & resources
[ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
Code and data for the paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning"
This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
[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
An benchmark for evaluating the capabilities of large vision-language models (LVLMs)
🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).
Talk2BEV: Language-Enhanced Bird's Eye View Maps (Accepted to ICRA'24)
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.
Curated papers on Large Language Models in Healthcare and Medical domain
[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
✨✨Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
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