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Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation
Chenyu Wang, Weichao Zhou, Shantanu Ghosh +2
Radiology report generation (RRG) has shown great potential in assisting radiologists by automating the labor-intensive task of report writing. While recent advancements have impro…
Distributionally robust self-supervised learning for tabular data
Shantanu Ghosh, Tiankang Xie, Mikhail Kuznetsov
Machine learning (ML) models trained using Empirical Risk Minimization (ERM) often exhibit systematic errors on specific subpopulations of tabular data, known as error slices. Lear…
LADDER: Language-Driven Slice Discovery and Error Rectification in Vision Classifiers
Shantanu Ghosh, Rayan Syed, Chenyu Wang +5
Error slice discovery is crucial to diagnose and mitigate model errors. Current clustering or discrete attribute-based slice discovery methods face key limitations: 1) clustering r…
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
Shantanu Ghosh, Clare B. Poynton, Shyam Visweswaran +1
The lack of large and diverse training data on Computer-Aided Diagnosis (CAD) in breast cancer detection has been one of the concerns that impedes the adoption of the system. Recen…