| Quantum entanglement in deep learning architectures Y Levine, O Sharir, N Cohen, A Shashua Physical review letters 122 (6), 065301, 2019 | 227 | 2019 |
| Deep autoregressive models for the efficient variational simulation of many-body quantum systems O Sharir, Y Levine, N Wies, G Carleo, A Shashua Physical review letters 124 (2), 020503, 2020 | 208 | 2020 |
| Sensebert: Driving some sense into bert Y Levine, B Lenz, O Dagan, D Padnos, O Sharir, S Shalev-Shwartz, ... Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 196 | 2020 |
| Deep learning and quantum entanglement: Fundamental connections with implications to network design Y Levine, D Yakira, N Cohen, A Shashua 6th International Conference on Learning Representations (ICLR), 2018 | 133* | 2018 |
| In-context retrieval-augmented language models O Ram, Y Levine, I Dalmedigos, D Muhlgay, A Shashua, K Leyton-Brown, ... arXiv preprint arXiv:2302.00083, 2023 | 60 | 2023 |
| PMI-Masking: Principled masking of correlated spans Y Levine, B Lenz, O Lieber, O Abend, K Leyton-Brown, M Tennenholtz, ... 9th International Conference on Learning Representations (ICLR), 2021 | 47 | 2021 |
| Analysis and design of convolutional networks via hierarchical tensor decompositions N Cohen, O Sharir, Y Levine, R Tamari, D Yakira, A Shashua arXiv preprint arXiv:1705.02302, 2017 | 41 | 2017 |
| Fundamental limitations of alignment in large language models Y Wolf, N Wies, Y Levine, A Shashua arXiv preprint arXiv:2304.11082, 2023 | 39 | 2023 |
| Limits to Depth Efficiencies of Self-Attention Y Levine, N Wies, O Sharir, H Bata, A Shashua Advances in Neural Information Processing Systems 34 (NeurIPS), 2020 | 39* | 2020 |
| Standing on the shoulders of giant frozen language models Y Levine, I Dalmedigos, O Ram, Y Zeldes, D Jannai, D Muhlgay, Y Osin, ... arXiv preprint arXiv:2204.10019, 2022 | 36 | 2022 |
| MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning E Karpas, O Abend, Y Belinkov, B Lenz, O Lieber, N Ratner, Y Shoham, ... arXiv preprint arXiv:2205.00445, 2022 | 28 | 2022 |
| Benefits of depth for long-term memory of recurrent networks Y Levine, O Sharir, A Shashua 6th International Conference on Learning Representations (ICLR) workshop, 2018 | 26* | 2018 |
| The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design Y Levine, N Wies, D Jannai, D Navon, Y Hoshen, A Shashua 10th International Conference on Learning Representations (ICLR), 2022 | 19 | 2022 |
| Realizing topological superconductivity with superlattices Y Levine, A Haim, Y Oreg Physical Review B 96 (16), 165147, 2017 | 18 | 2017 |
| The learnability of in-context learning N Wies, Y Levine, A Shashua arXiv preprint arXiv:2303.07895, 2023 | 15 | 2023 |
| Tensors for deep learning theory: Analyzing deep learning architectures via tensorization Y Levine, N Wies, O Sharir, N Cohen, A Shashua Tensors for Data Processing, 215-248, 2022 | 14* | 2022 |
| Sub-task decomposition enables learning in sequence to sequence tasks N Wies, Y Levine, A Shashua ICLR 2023, 2023 | 12 | 2023 |
| Which transformer architecture fits my data? a vocabulary bottleneck in self-attention N Wies, Y Levine, D Jannai, A Shashua International Conference on Machine Learning, 11170-11181, 2021 | 12 | 2021 |
| Generating benchmarks for factuality evaluation of language models D Muhlgay, O Ram, I Magar, Y Levine, N Ratner, Y Belinkov, O Abend, ... arXiv preprint arXiv:2307.06908, 2023 | 9 | 2023 |
| Parallel context windows for large language models N Ratner, Y Levine, Y Belinkov, O Ram, I Magar, O Abend, E Karpas, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 9* | 2023 |
Amnon ShashuaProfessor of Computer Science, the Hebrew University of JerusalemVerified email at cs.huji.ac.il
