
Itay Itzhak
I'm interested in
About
I am a PhD candidate at the Technion, lucky to be
co-advised by Yonatan Belinkov and Gabriel Stanovsky at the Hebrew University in Jerusalem.
My research focuses on evaluating and interpreting LLMs, with particular interest in
the reasoning and decision-making processes that underlie their behavior, including failures that reveal
human-like cognitive biases. My work combines behavioral and representational analyses to better understand
model tendencies and the impact
of fine-tuning and pretraining.
I previously interned at Meta AI,
where I studied attention dynamics in translation models, and completed my M.Sc. at Tel Aviv University with Omer Levy, where I investigated how token-level spelling
information is encoded in embedding matrices.
Beyond model analysis, I co-organized the GEM workshop at ACL
2025, which aims to establish best practices for the evaluation of natural language generation systems across
languages and tasks. I am also an active contributor to the EvalEval
coalition, a community initiative to standardize and compare evaluation outputs across frameworks, promoting
robust, scalable, and scientifically grounded evaluation practices.
I am always open to collaborations and enjoy discussing research, language models, and everything in between.
Feel free to reach out via email!
Publications
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs
Itay Itzhak, Yonatan Belinkov, Gabriel Stanovsky
CoLM 2025
[Code] / [Webpage]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
ACL 2025
[Code] / [Webpage]Trust Me, I'm Wrong: High-Certainty Hallucinations in LLMs
Adi Simhi, Itay Itzhak, Fazl Barez, Gabriel Stanovsky, Yonatan Belinkov
EMNLP 2025
[Code]Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias
Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov
TACL 2024
[Code]Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens
Itay Itzhak, Omer Levy
NAACL 2022
[Code] / [Talk]The impact of tumor detection method on genomic and clinical risk and chemotherapy recommendation in early hormone receptor positive breast cancer
Yael Bar, Kfir Bar, Itay Itzhak, Chen Shitrit Niselbaum, N. Dershowitz, E. Shachar, A. Weiss-Meilik, O. Golan, I. Wolf, T. Menes, A. Sonnenblick