| In-context retrieval-augmented language models O Ram, Y Levine, I Dalmedigos, D Muhlgay, A Shashua, K Leyton-Brown, ... Transactions of the Association for Computational Linguistics 11, 1316-1331, 2023 | 318 | 2023 |
| Quantum entanglement in deep learning architectures Y Levine, O Sharir, N Cohen, A Shashua Physical review letters 122 (6), 065301, 2019 | 265 | 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 | 248 | 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 | 230 | 2020 |
| Fundamental limitations of alignment in large language models Y Wolf, N Wies, O Avnery, Y Levine, A Shashua arXiv preprint arXiv:2304.11082, 2023 | 149 | 2023 |
| 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 | 142 | 2018 |
| Parallel context windows for large language models N Ratner, Y Levine, Y Belinkov, O Ram, I Magar, O Abend, E Karpas, ... arXiv preprint arXiv:2212.10947, 2022 | 62 | 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 | 61 | 2022 |
| 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 | 60 | 2021 |
| 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 | 53* | 2020 |
| The learnability of in-context learning N Wies, Y Levine, A Shashua Advances in Neural Information Processing Systems 36, 2024 | 51 | 2024 |
| 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 | 46 | 2023 |
| 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 | 44 | 2017 |
| 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 | 43 | 2022 |
| 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 | 33 | 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 | 32* | 2018 |
| 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 | 28* | 2022 |
| Human or Not? A gamified approach to the Turing test D Jannai, A Meron, B Lenz, Y Levine, Y Shoham arXiv preprint arXiv:2305.20010, 2023 | 22 | 2023 |
| Sub-task decomposition enables learning in sequence to sequence tasks N Wies, Y Levine, A Shashua ICLR 2023, 2023 | 22 | 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 | 20 | 2021 |
Amnon ShashuaProfessor of Computer Science, the Hebrew University of JerusalemVerified email at cs.huji.ac.il
