EAGLE: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

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

[EMNLP 2024 Industry Track] This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".

[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

Large Visual Language Model(LVLM), Large Language Model(LLM), Multimodal Large Language Model(MLLM), Alignment, Agent, AI System, Survey

CLIP-MoE: Mixture of Experts for CLIP

A benchmark dataset and simple code examples for measuring the perception and reasoning of multi-sensor Vision Language models.

HiRED strategically drops visual tokens in the image encoding stage to improve inference efficiency for High-Resolution Vision-Language Models (e.g., LLaVA-Next) under a fixed token budget.

LEMMA: An effective and explainable way to detect multimodal misinformation with LVLM and external knowledge augmentation, incorporating the intuition and reasoning capbility inside LVLM.

Code for USENIX Security 2024 paper: Moderating Illicit Online Image Promotion for Unsafe User Generated Content Games Using Large Vision-Language Models.

Novel approach that leverages LVLMs to efficiently generate high-quality synthetic VQA-NLE datasets.

A powerful Streamlit application that allows users to analyze and interact with YouTube video content through natural language questions.