activity
20242026
collaborators

11 papers

cs.CL2026

Empty Shelves or Lost Keys? Recall Is the Bottleneck for Parametric Factuality

Nitay Calderon, Eyal Ben-David, Zorik Gekhman +2

Standard factuality evaluations of LLMs treat all errors alike, obscuring whether failures arise from missing knowledge (empty shelves) or from limited access to encoded facts (los…

cs.CL2026

Thinking to Recall: How Reasoning Unlocks Parametric Knowledge in LLMs

Zorik Gekhman, Roee Aharoni, Eran Ofek +3

While reasoning in LLMs plays a natural role in math, code generation, and multi-hop factual questions, its effect on simple, single-hop factual questions remains unclear. Such que…

cs.CL2026

Evaluating Alignment of Behavioral Dispositions in LLMs

Amir Taubenfeld, Zorik Gekhman, Lior Nezry +8

As LLMs integrate into our daily lives, understanding their behavior becomes essential. In this work, we focus on behavioral dispositionsthe underlying tendencies that shape res…

cs.CL2025

HACK: Hallucinations Along Certainty and Knowledge Axes

Adi Simhi, Jonathan Herzig, Itay Itzhak +7

Hallucinations in LLMs present a critical barrier to their reliable usage. Existing research usually categorizes hallucination by their external properties rather than by the LLMs'…

cs.CL2025

Fine-Grained Detection of Context-Grounded Hallucinations Using LLMs

Yehonatan Peisakhovsky, Zorik Gekhman, Yosi Mass +2

Context-grounded hallucinations are cases where model outputs contain information not verifiable against the source text. We study the applicability of LLMs for localizing such hal…

cs.CL2025

Confidence Improves Self-Consistency in LLMs

Amir Taubenfeld, Tom Sheffer, Eran Ofek +4

Self-consistency decoding enhances LLMs' performance on reasoning tasks by sampling diverse reasoning paths and selecting the most frequent answer. However, it is computationally e…