2 citations · 3 across the 11 of their papers we have counts for
8 papers · 1 filter
DeepAffinity: Long-Term Aspect Preference Prediction in eCommerce using Small Language Models
Yotam Eshel, Guy Hadad, Guy Feigenblat +3
We explore predicting eCommerce user preferences for product aspects such as brand, size, and color - a task we define as Aspect Affinity. Solving this task improves customer under…
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…
SHAPoint: Task-Agnostic, Efficient, and Interpretable Point-Based Risk Scoring via Shapley Values
Tomer D. Meirman, Bracha Shapira, Noa Dagan +1
Interpretable risk scores play a vital role in clinical decision support, yet traditional methods for deriving such scores often rely on manual preprocessing, task-specific modelin…
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM Performance
Seffi Cohen, Niv Goldshlager, Nurit Cohen-Inger +2
Large Language Models (LLMs) have shown remarkable capabilities across various natural language processing tasks but often struggle to excel uniformly in diverse or complex domains…
FairTTTS: A Tree Test Time Simulation Method for Fairness-Aware Classification
Nurit Cohen-Inger, Lior Rokach, Bracha Shapira +1
Algorithmic decision-making has become deeply ingrained in many domains, yet biases in machine learning models can still produce discriminatory outcomes, often harming unprivileged…
BiasGuard: Guardrailing Fairness in Machine Learning Production Systems
Nurit Cohen-Inger, Seffi Cohen, Neomi Rabaev +2
As machine learning (ML) systems increasingly impact critical sectors such as hiring, financial risk assessments, and criminal justice, the imperative to ensure fairness has intens…