collaborators

8 papers

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

ManagerBench: Evaluating the Safety-Pragmatism Trade-off in Autonomous LLMs

Adi Simhi, Jonathan Herzig, Martin Tutek +3

As large language models (LLMs) evolve from conversational assistants into autonomous agents, evaluating the safety of their actions becomes critical. Prior safety benchmarks have…

cs.CL2026

Latent Reasoning with Supervised Thinking States

Ido Amos, Avi Caciularu, Mor Geva +4

Reasoning with a chain-of-thought (CoT) enables Large Language Models (LLMs) to solve complex tasks but incurs significant inference costs due to the generation of long rationales.…

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

DoubleDipper: Improving Long-Context LLMs via Context Recycling

Arie Cattan, Alon Jacovi, Alex Fabrikant +8

Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal. In this work, we propose DoubleDipper, a novel…

cs.CL2025

DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs

Arie Cattan, Alon Jacovi, Ori Ram +6

Retrieval Augmented Generation (RAG) is a commonly used approach for enhancing large language models (LLMs) with relevant and up-to-date information. However, the retrieved sources…