Deep autoregressive models for the efficient variational simulation of many-body quantum systems. - Or Sharir; Yoav Levine; Noam Wies; Giuseppe Carleo; Amnon Shashua (CoRR, 2019)

Limits to Depth Efficiencies of Self-Attention. - Yoav Levine; Noam Wies; Or Sharir; Hofit Bata; Amnon Shashua (NeurIPS, 2020)

Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. - Noam Wies; Yoav Levine; Daniel Jannai; Amnon Shashua (ICML, 2021)

The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. - Yoav Levine; Noam Wies; Daniel Jannai; Dan Navon; Yedid Hoshen; Amnon Shashua (ICLR, 2022)

Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. - Noam Wies; Yoav Levine; Amnon Shashua (ICLR, 2023)

The Learnability of In-Context Learning. - Noam Wies; Yoav Levine; Amnon Shashua (NeurIPS, 2023)

Fundamental Limitations of Alignment in Large Language Models. - Yotam Wolf; Noam Wies; Yoav Levine; Amnon Shashua (CoRR, 2023)

Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework. - Eliya Segev; Maya Alroy; Ronen Katsir; Noam Wies; Ayana Shenhav; Yael Ben-Oren; David Zar; Oren Tadmor; Jacob Bitterman; Amnon Shashua; Tal Rosenwein (ICLR, 2024)

Fundamental Limitations of Alignment in Large Language Models. - Yotam Wolf; Noam Wies; Oshri Avnery; Yoav Levine; Amnon Shashua (ICML, 2024)

Tradeoffs Between Alignment and Helpfulness in Language Models. - Yotam Wolf; Noam Wies; Dorin Shteyman; Binyamin Rothberg; Yoav Levine; Amnon Shashua (CoRR, 2024)

Artificial Expert Intelligence through PAC-reasoning. - Shai Shalev-Shwartz; Amnon Shashua; Gal Beniamini; Yoav Levine; Or Sharir; Noam Wies; Ido Ben-Shaul; Tomer Nussbaum; Shir Granot Peled (CoRR, 2024)

FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming. - Gal Beniamini; Yuval Dor; Alon Vinnikov; Shir Granot Peled; Or Weinstein; Or Sharir; Noam Wies; Tomer Nussbaum; Ido Ben-Shaul; Tomer Zekharya; Yoav Levine; Shai Shalev-Shwartz; et al. (CoRR, 2025)