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Starred repositories
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[ICLR'25] MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
[ICLR'25] Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
[ICLR 2025] Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contā¦
Awesome-RAG-Vision: a curated list of advanced retrieval augmented generation (RAG) for Computer Vision
[CVPR 2025] Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question Answering
[EMNLP'24] RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
[Nature Reviews Bioengineeringš„] Application of Large Language Models in Medicine. A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)
[ICLR 2025] This is the official repository of our paper "MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicineā
m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning in Large Language Models
Towards Medical Small Language Models with Self-Evolved \\ Slow Thinking
[NeurIPS 2024] MoVA: Adapting Mixture of Vision Experts to Multimodal Context
Some Conferences' accepted paper lists (including AI, ML, Robotic)
š« CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image
[CVPR'25] Enhanced Contrastive Learning with Multi-view Longitudinal Data for Chest X-ray Report Generation
MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
[ISMB '24] Self-BioRAG: Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models
Repo for the pape Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions
MICCAI24: A Universal and Flexible Framework for Unsupervised Statistical Shape Model Learning
[CVPR 2024] Generalizable Tumor Synthesis - Realistic Synthetic Tumors in Liver, Pancreas, and Kidney
(TMI-2024) Source-Free Active Domain Adaptation (SFADA) for GTV Segmentation across Multiple Hospitals
[MICCAI 2024] Anatomically-Guided Segmentation of Cerebral Microbleeds in T1-weighted and T2*-weighted MRI
Medical o1, Towards medical complex reasoning with LLMs
Agent benchmark for medical diagnosis