Projects sharing features with LLaVA Med

Open-sourced code of MiniGPT-Med

This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of large language models. It serves as a structured natural language processing resource, offering a collection of text data that includes dialogue, customer service interactions, and creative writing. The dataset is organized into distinct thematic categories, allowing for targeted model development across specific conversational and narrative contexts. By providing information in standardized, schema-agnostic text formats, the collection ensures portability across various machine l

demo:https://github.com/BAAI-DCAI/M3D/blob/main/LaMed/src/demo/online_demo.py

Aofei Chang, Le Huang, Alex James Boyd, Parminder Bhatia, Taha Kass-Hout, Cao Xiao, Fenglong Ma

Generated by DALL·E 3

Official code for the Paper "RaDialog: A Large Vision-Language Model for Radiology Report Generation and Conversational Assistance"

The official code for "Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data".

M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization), MICCAI 2023.

NEWS!This paper has been accpeted by MICCAI 2023 Sorry that I had the autumn recruitment in China a few months ago, and I did not update the open source trend of the paper. I have found a satisfactory job and returned to scientific research yet!! Remaining code is being updated per week !!

Kun Yuan, Vinkle Srivastav, Tong Yu, Joel L. Lavanchy, Pietro Mascagni, Nassir Navab, Nicolas Padoy

Speedup Volume Understanding with Efficient Multimodal Large Language Models

EyecareGPT: Boosting Comprehensive Ophthalmology Understanding with Tailored Dataset, Benchmark and Model

🤖 Model | 🤗 Dataset | 📖 Paper

We developed a domain-speciffc large language-vision assistant (PA-LLaVA) for pathology image understanding. Specifically, (1) we first construct a human pathology image-text dataset by cleaning the public medical image-text data for domainspecific alignment; (2) Using the proposed image-text…

This repository contains the official implementation for benchmarking various Direct Preference Optimization (DPO) methodologies on Medical Large Vision-Language Models (VLMs).

MedVH is a dataset for evaluating hallucination in large vision language models on medical visual question answering tasks, specifically with chest x-ray images. This repository provides part of the dataset, which is proposed in our paper "MedVH: Towards Systematic Evaluation of Hallucination…

Project Page for "LISA: Reasoning Segmentation via Large Language Model"

MNBVC is a dataset pipeline and toolkit designed for the collection, cleaning, and normalization of massive text and code corpora used to train large language models. It provides specialized tools for harvesting source code, commit histories, and repository metadata from version control platforms, alongside a multilingual text corpus collector for gathering parallel text and academic papers. The project distinguishes itself through comprehensive capabilities for processing diverse document types, including a PDF-to-text converter that transforms complex layouts and formulas into structured JS

MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025

ShizhenGPT

```zsh git clone --recursive https://github.com/function2-llx/MMMM.git cd MMMM mamba env create -f environment.yaml BUILDMONAI=1 pip install --no-build-isolation -e third-party/LuoLib/third-party/MONAI mamba activate mmmm echo \ "export PYTHONPATH=$PWD:$PWD/third-party/LuoLib export BUILDMONAI=1" \

ICLR'24 Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

torch >= 1.11.0