68 citations · 68 across the 4 of their papers we have counts for
5 papers
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
Adriel Saporta, Aahlad Puli, Mark Goldstein +1
Contrastive learning methods, such as CLIP, leverage naturally paired data-for example, images and their corresponding text captions-to learn general representations that transfer…
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation
Neil Jethani, Adriel Saporta, Rajesh Ranganath
Feature attribution methods identify which features of an input most influence a model's output. Most widely-used feature attribution methods (such as SHAP, LIME, and Grad-CAM) are…
Learning Invariant Representations with Missing Data
Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau +4
Spurious correlations allow flexible models to predict well during training but poorly on related test distributions. Recent work has shown that models that satisfy particular inde…
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management
Cécile Logé, Emily Ross, David Yaw Amoah Dadey +4
Recent advances in Natural Language Processing (NLP), and specifically automated Question Answering (QA) systems, have demonstrated both impressive linguistic fluency and a pernici…
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
Saahil Jain, Ashwin Agrawal, Adriel Saporta +9
Extracting structured clinical information from free-text radiology reports can enable the use of radiology report information for a variety of critical healthcare applications. In…