large-vision-language-models

✨✨Latest Advances on Multimodal Large Language Models

[NeurIPS 2024] An official implementation of ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation

✨✨[CVPR 2025] Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).

The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.

Curated papers on Large Language Models in Healthcare and Medical domain

[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

[ECCV 2024] ShareGPT4V: Improving Large Multi-modal Models with Better Captions

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.

[NeurIPS 2024] This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"

up-to-date curated list of state-of-the-art Large vision language models hallucinations research work, papers & resources

Talk2BEV: Language-Enhanced Bird's Eye View Maps (ICRA'24)

[ECCV 2024] API: Attention Prompting on Image for 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.

GeoPixel: A Pixel Grounding Large Multimodal Model for Remote Sensing is specifically developed for high-resolution remote sensing image analysis, offering advanced multi-target pixel grounding capabilities.

[ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.

An benchmark for evaluating the capabilities of large vision-language models (LVLMs)

✨A curated list of papers on the uncertainty in multi-modal large language model (MLLM).

This repository is the codebase of TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy