7 citations · 22 across the 20 of their papers we have counts for
5 papers · 1 filter
Leveraging NTPs for Efficient Hallucination Detection in VLMs
Ofir Azachi, Kfir Eliyahu, Eyal El Ani +4
Hallucinations of vision-language models (VLMs), which are misalignments between visual content and generated text, undermine the reliability of VLMs. One common approach for detec…
Multi-Domain Explainability of Preferences
Nitay Calderon, Liat Ein-Dor, Roi Reichart
Preference mechanisms, such as human preference, LLM-as-a-Judge (LaaJ), and reward models, are central to aligning and evaluating large language models (LLMs). Yet, the underlying…
Dementia Through Different Eyes: Explainable Modeling of Human and LLM Perceptions for Early Awareness
Lotem Peled-Cohen, Maya Zadok, Nitay Calderon +2
Cognitive decline often surfaces in language years before diagnosis. It is frequently non-experts, such as those closest to the patient, who first sense a change and raise concern.…
AdaptiVocab: Enhancing LLM Efficiency in Focused Domains through Lightweight Vocabulary Adaptation
Itay Nakash, Nitay Calderon, Eyal Ben David +2
Large Language Models (LLMs) have shown impressive versatility as general purpose models. However, their broad applicability comes at a high-cost computational overhead, particular…
The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs
Nitay Calderon, Roi Reichart, Rotem Dror
The "LLM-as-an-annotator" and "LLM-as-a-judge" paradigms employ Large Language Models (LLMs) as annotators, judges, and evaluators in tasks traditionally performed by humans. LLM a…