4 papers
CRANE: Post-Hoc Counterfactual Retrieval for Multimodal Classifiers
Franco Rugolon, Ioanna Miliou, Panagiotis Papapetrou
Counterfactual explanation methods have been introduced for unimodal settings, with dedicated frameworks for tabular, timeseries, text, and image data, yet no post-hoc method has b…
SurvCF(t): Counterfactual Explanations for Survival Analysis in Predictive Maintenance Multivariate Time Series Data
Zara Karazian, Panagiotis Papapetrou, Sindri Magnússon +2
Predictive maintenance relies on accurate Remaining Useful Life estimation, often formulated using survival analysis over multivariate time-series data. While modern deep survival…
Multimodal Machine Learning for Early Prediction of Metastasis in a Swedish Multi-Cancer Cohort
Franco Rugolon, Korbinian Randl, Braslav Jovanovic +2
Multimodal Machine Learning offers a holistic view of a patient's status, integrating structured and unstructured data from electronic health records (EHR). We propose a framework…
CHiL(L)Grader: Calibrated Human-in-the-Loop Short-Answer Grading
Pranav Raikote, Korbinian Randl, Ioanna Miliou +2
Scaling educational assessment with large language models requires not just accuracy, but the ability to recognize when predictions are trustworthy. Instruction-tuned models tend t…