6 citations · 8 across the 10 of their papers we have counts for
7 papers · 2 filters
BlackboxNLP-2025 MIB Shared Task: Improving Circuit Faithfulness via Better Edge Selection
Yaniv Nikankin, Dana Arad, Itay Itzhak +4
One of the main challenges in mechanistic interpretability is circuit discovery, determining which parts of a model perform a given task. We build on the Mechanistic Interpretabili…
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'…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
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…
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs
Itay Itzhak, Yonatan Belinkov, Gabriel Stanovsky
Large language models (LLMs) exhibit cognitive biases -- systematic tendencies of irrational decision-making, similar to those seen in humans. Prior work has found that these biase…
DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation
Eliya Habba, Ofir Arviv, Itay Itzhak +5
Recent work found that LLMs are sensitive to a wide range of arbitrary prompt dimensions, including the type of delimiters, answer enumerators, instruction wording, and more. This…
Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer
Adi Simhi, Itay Itzhak, Fazl Barez +2
Prior work on large language model (LLM) hallucinations has associated them with model uncertainty or inaccurate knowledge. In this work, we define and investigate a distinct type…