1 citations · 2 across the 4 of their papers we have counts for
5 papers
Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
Kimia Hamidieh, Veronika Thost, Walter Gerych +2
Large language models (LLMs) often produce confident yet incorrect responses, and uncertainty quantification is one potential solution to more robust usage. Recent works routinely…
An Investigation of Memorization Risk in Healthcare Foundation Models
Sana Tonekaboni, Lena Stempfle, Adibvafa Fallahpour +2
Foundation models trained on large-scale de-identified electronic health records (EHRs) hold promise for clinical applications. However, their capacity to memorize patient informat…
The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making
Abinitha Gourabathina, Yuexing Hao, Walter Gerych +1
Clinical robustness is critical to the safe deployment of medical Large Language Models (LLMs), but key questions remain about how LLMs and humans may differ in response to the rea…
MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations
Qixuan Jin, Walter Gerych, Marzyeh Ghassemi
Spurious features associated with class labels can lead image classifiers to rely on shortcuts that don't generalize well to new domains. This is especially problematic in medical…
BendVLM: Test-Time Debiasing of Vision-Language Embeddings
Walter Gerych, Haoran Zhang, Kimia Hamidieh +4
Vision-language model (VLM) embeddings have been shown to encode biases present in their training data, such as societal biases that prescribe negative characteristics to members o…