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Found 2 papers, 1 papers with code
Understanding and Alleviating Memory Consumption in RLHF for LLMs
Fine-tuning with Reinforcement Learning with Human Feedback (RLHF) is essential for aligning large language models (LLMs).
A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis
Unlike previous CXR computer-aided diagnosis works that focused on disease diagnosis/classification, we firstly propose a deep disentangled generative model (DGM) simultaneously generating abnormal disease residue maps and “radiorealistic” normal CXR images from an input abnormal CXR image.
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