5 papers
MedUPS: Towards Diagnostic Assistance in Uncommon Medical Cases with Large Language Models
Ofir Ben Shoham, Oriel Perets, Nir Grinberg +1
Uncommon and off-guideline cases are difficult for clinical decision support, because physicians must make a series of management decisions under diagnostic uncertainty and rarely…
Cluster Frequency Conformal Prediction for Local Coverage
Tomer Lavi, Bracha Shapira, Nadav Rappoport
Conformal prediction provides distribution-free coverage guarantees, but in many-class classification it may still under-cover specific classes or subpopulations, preventing safe d…
Trajectory-Based Difficulty Scoring for Reliable Learning on Tabular Data
Tomer Lavi, Bracha Shapira, Nadav Rappoport
Gradient-boosted trees achieve strong performance on tabular data, yet often leave a long tail of poorly predicted instances. We introduce a Trajectory-based Difficulty Score (TDS)…
Clustered Calibration: Representation-Aware Probability Calibration via Learned Subpopulations
Tomer Lavi, Bracha Shapira, Nadav Rappoport
Ensuring that predicted probabilities align with observed frequencies is critical in high-stakes domains such as clinical decision support, autonomous driving and financial risk as…
ProtSent: Protein Sentence Transformers
Dan Ofer, Oriel Perets, Michal Linial +1
Protein language models (pLMs) produce per-residue representations that capture evolutionary and structural information, yet their mean-pooled sequence embeddings are not explicitl…