CheXGenBench: A Unified Benchmark For Fidelity, Privacy and Utility of Synthetic Chest Radiographs Paper • 2505.10496 • Published about 1 month ago • 2
Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities Paper • 2503.22517 • Published Mar 28
BMFT: Achieving Fairness via Bias-based Weight Masking Fine-tuning Paper • 2408.06890 • Published Aug 13, 2024
The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation Paper • 2502.07516 • Published Feb 11 • 1
MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter Selection Paper • 2405.19458 • Published May 29, 2024
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models Paper • 2402.02207 • Published Feb 3, 2024 • 2
VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning Paper • 2403.13164 • Published Mar 19, 2024 • 1
Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted Paper • 2406.18566 • Published Jun 1, 2024 • 1
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor? Paper • 2409.15277 • Published Sep 23, 2024 • 39
Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning Paper • 2406.12742 • Published Jun 18, 2024 • 15
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis Paper • 2310.05055 • Published Oct 8, 2023 • 1
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity Paper • 2305.08252 • Published May 14, 2023