---
base_model:
- google/diffusiongemma-26B-A4B-it
- google/gemma-4-26B-A4B-it
library_name: peft
license: apache-2.0
pipeline_tag: image-text-to-text
tags:
- medical
- radiology
- vqa
- medical-imaging
- lora
- diffusion-llm
---

# DiffusionGemma finetunes for radiology VQA

This repository contains LoRA finetunes of **DiffusionGemma** (image-conditioned discrete-diffusion LLM) for radiology visual question answering, each paired with an **autoregressive Gemma-4** finetune as a controlled baseline. It corresponds to the paper [Discrete Diffusion Language Models for Interactive Radiology Report Drafting](https://huggingface.co/papers/2607.01436).

The dataset covers mixed modalities/anatomy (VQA-RAD, SLAKE, VQA-Med: X-ray/CT/MRI, head/chest/abdomen). Judge-best checkpoint per cell.

**Code:** https://github.com/mxvp/discrete_diffusion_RRG

| subfolder | backbone | base model | dataset | LLM-judge acc |
|---|---|---|---|---|
| diffusion-vqarad | discrete-diffusion | google/diffusiongemma-26B-A4B-it | VQA-RAD | 0.649  |
| ar-vqarad | autoregressive | google/gemma-4-26B-A4B-it | VQA-RAD | 0.649 |
| diffusion-slake | discrete-diffusion | google/diffusiongemma-26B-A4B-it | SLAKE | 0.863 |
| ar-slake | autoregressive |  google/gemma-4-26B-A4B-it | SLAKE | 0.817 |
| diffusion-vqamed | discrete-diffusion | google/diffusiongemma-26B-A4B-it | VQA-Med | 0.666 |
| ar-vqamed | autoregressive | google/gemma-4-26B-A4B-it | VQA-Med | 0.631 |