An benchmark for evaluating the capabilities of large vision-language models (LVLMs)
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Updated
Nov 17, 2023 - Python
An benchmark for evaluating the capabilities of large vision-language models (LVLMs)
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Talk2BEV: Language-Enhanced Bird's Eye View Maps (Accepted to ICRA'24)
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
[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"
[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
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
Multi-Agent VQA: Exploring Multi-Agent Foundation Models on Zero-Shot Visual Question Answering
This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"
🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).
✨✨Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
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
up-to-date and curated list of awesome state-of-the-art LVLMs hallucinations research work, papers & resources
[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
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