Image-to-Text
PEFT
Safetensors
medical-imaging
chest-xray
dermoscopy
vision-language
fairness
lora
mimic-cxr
padchest
ham10000
Instructions to use mbhosale/FairLLaVA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mbhosale/FairLLaVA with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -29,7 +29,7 @@ Fairness-aware LoRA adapters for medical vision–language models, from the
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- **Paper**: [arxiv.org/abs/2603.26008](https://arxiv.org/abs/2603.26008)
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FairLLaVA minimizes the mutual information between the model's visual
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features and patient demographic attributes (age, sex, race
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producing demographic-invariant representations while preserving clinical
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accuracy. The adapters here plug into a standard LoRA fine-tuning loop and
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are released on three medical benchmarks.
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- **Paper**: [arxiv.org/abs/2603.26008](https://arxiv.org/abs/2603.26008)
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FairLLaVA minimizes the mutual information between the model's visual
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features and patient demographic attributes (age, sex, race),
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producing demographic-invariant representations while preserving clinical
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| 34 |
accuracy. The adapters here plug into a standard LoRA fine-tuning loop and
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| 35 |
are released on three medical benchmarks.
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