Itay Itzhak

According to our database, Itay Itzhak authored at least 12 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs.

Itay Itzhak, Eliya Habba, Gabriel Stanovsky, Yonatan Belinkov

CoRR, April, 2026

Growing Pains: Extensible and Efficient LLM Benchmarking Via Fixed Parameter Calibration.

Eliya Habba, Itay Itzhak, Asaf Yehudai, Yotam Perlitz, Elron Bandel, Michal Shmueli-Scheuer, Leshem Choshen, Gabriel Stanovsky

CoRR, April, 2026

2025

BlackboxNLP-2025 MIB Shared Task: Improving Circuit Faithfulness via Better Edge Selection.

Yaniv Nikankin, Dana Arad, Itay Itzhak, Anja Reusch, Adi Simhi, Gal Kesten-Pomeranz, Yonatan Belinkov

CoRR, October, 2025

HACK: Hallucinations Along Certainty and Knowledge Axes.

Adi Simhi, Jonathan Herzig, Itay Itzhak, Dana Arad, Zorik Gekhman, Roi Reichart, Fazl Barez, Gabriel Stanovsky, Idan Szpektor, Yonatan Belinkov

CoRR, October, 2025

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

Adi Simhi, Jonathan Herzig, Martin Tutek, Itay Itzhak, Idan Szpektor, Yonatan Belinkov

CoRR, October, 2025

Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs.

Itay Itzhak, Yonatan Belinkov, Gabriel Stanovsky

CoRR, July, 2025

Trust Me, I'm Wrong: High-Certainty Hallucinations in LLMs.

Adi Simhi, Itay Itzhak, Fazl Barez, Gabriel Stanovsky, Yonatan Belinkov

CoRR, February, 2025

Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer.

Adi Simhi, Itay Itzhak, Fazl Barez, Gabriel Stanovsky, Yonatan Belinkov

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation.

Eliya Habba, Ofir Arviv, Itay Itzhak, Yotam Perlitz, Elron Bandel, Leshem Choshen, Michal Shmueli-Scheuer, Gabriel Stanovsky

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2023

Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias.

Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov

CoRR, 2023

2022

Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens.

Itay Itzhak, Omer Levy

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Evaluating locality in NMT models.

Itay Itzhak, Koustuv Sinha, Brenden M. Lake, Adina Williams, Dieuwke Hupkes

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022