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Noam Wies
Noam Wies
Verified email at cs.huji.ac.il
Title
Cited by
Cited by
Year
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
2252020
Fundamental Limitations of Alignment in Large Language Models
Y Wolf, N Wies, Y Levine, A Shashua
arXiv preprint arXiv:2304.11082, 2023
832023
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
46*2020
The learnability of in-context learning
N Wies, Y Levine, A Shashua
Advances in Neural Information Processing Systems 36, 2024
292024
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), 2021
262021
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
N Wies, Y Levine, A Shashua
11th International Conference on Learning Representations (ICLR), 2022
172022
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
172021
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
22022
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
E Segev, M Alroy, R Katsir, N Wies, A Shenhav, Y Ben-Oren, D Zar, ...
arXiv preprint arXiv:2307.01715, 2023
12023
Tradeoffs Between Alignment and Helpfulness in Language Models
Y Wolf, N Wies, D Shteyman, B Rothberg, Y Levine, A Shashua
arXiv preprint arXiv:2401.16332, 2024
2024
Implicit Intermediate Supervision for Learning Complex Functions
E Malach, G Kaplun, N Wies
2023
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