105 citations · 501 across the 65 of their papers we have counts for
7 papers · 1 filter
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…
Dark LLMs: The Growing Threat of Unaligned AI Models
Michael Fire, Yitzhak Elbazis, Adi Wasenstein +1
Large Language Models (LLMs) rapidly reshape modern life, advancing fields from healthcare to education and beyond. However, alongside their remarkable capabilities lies a signific…
X-Cross: Dynamic Integration of Language Models for Cross-Domain Sequential Recommendation
Guy Hadad, Haggai Roitman, Yotam Eshel +2
As new products are emerging daily, recommendation systems are required to quickly adapt to possible new domains without needing extensive retraining. This work presents ``X-Cross'…
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…
Forget What You Know about LLMs Evaluations -- LLMs are Like a Chameleon
Nurit Cohen-Inger, Yehonatan Elisha, Bracha Shapira +2
Large language models (LLMs) often appear to excel on public benchmarks, but these high scores may mask an overreliance on dataset-specific surface cues rather than true language u…
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…