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Journal Articles
- 2023
[j1]Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
In-Context Retrieval-Augmented Language Models. Trans. Assoc. Comput. Linguistics 11: 1316-1331 (2023)
Conference and Workshop Papers
- 2024
- [c13]Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham:
Generating Benchmarks for Factuality Evaluation of Language Models. EACL (1) 2024: 49-66 - [c12]Narun Krishnamurthi Raman, Taylor Lundy, Samuel Joseph Amouyal, Yoav Levine, Kevin Leyton-Brown, Moshe Tennenholtz:
STEER: Assessing the Economic Rationality of Large Language Models. ICML 2024 - [c11]Yotam Wolf, Noam Wies, Oshri Avnery, Yoav Levine, Amnon Shashua:
Fundamental Limitations of Alignment in Large Language Models. ICML 2024 - 2023
- [c10]Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
Parallel Context Windows for Large Language Models. ACL (1) 2023: 6383-6402 - [c9]Noam Wies
, Yoav Levine, Amnon Shashua:
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. ICLR 2023 - [c8]Noam Wies, Yoav Levine, Amnon Shashua:
The Learnability of In-Context Learning. NeurIPS 2023 - 2022
- [c7]Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua:
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. ICLR 2022 - 2021
- [c6]Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham:
PMI-Masking: Principled masking of correlated spans. ICLR 2021 - [c5]Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua:
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. ICML 2021: 11170-11181 - 2020
- [c4]Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham:
SenseBERT: Driving Some Sense into BERT. ACL 2020: 4656-4667 - [c3]Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua:
Limits to Depth Efficiencies of Self-Attention. NeurIPS 2020 - 2018
- [c2]Yoav Levine, Or Sharir, Amnon Shashua:
Benefits of Depth for Long-Term Memory of Recurrent Networks. ICLR (Workshop) 2018 - [c1]Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua:
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. ICLR (Poster) 2018
Informal and Other Publications
- 2024
- [i21]Yotam Wolf, Noam Wies, Dorin Shteyman, Binyamin Rothberg, Yoav Levine, Amnon Shashua:
Tradeoffs Between Alignment and Helpfulness in Language Models. CoRR abs/2401.16332 (2024) - [i20]Narun K. Raman, Taylor Lundy, Samuel Joseph Amouyal, Yoav Levine, Kevin Leyton-Brown, Moshe Tennenholtz:
Rationality Report Cards: Assessing the Economic Rationality of Large Language Models. CoRR abs/2402.09552 (2024) - 2023
- [i19]Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
In-Context Retrieval-Augmented Language Models. CoRR abs/2302.00083 (2023) - [i18]Noam Wies, Yoav Levine, Amnon Shashua:
The Learnability of In-Context Learning. CoRR abs/2303.07895 (2023) - [i17]Yotam Wolf, Noam Wies, Yoav Levine, Amnon Shashua:
Fundamental Limitations of Alignment in Large Language Models. CoRR abs/2304.11082 (2023) - [i16]Daniel Jannai, Amos Meron, Barak Lenz, Yoav Levine, Yoav Shoham:
Human or Not? A Gamified Approach to the Turing Test. CoRR abs/2305.20010 (2023) - [i15]Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham:
Generating Benchmarks for Factuality Evaluation of Language Models. CoRR abs/2307.06908 (2023) - 2022
- [i14]Noam Wies, Yoav Levine, Amnon Shashua:
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. CoRR abs/2204.02892 (2022) - [i13]Yoav Levine, Itay Dalmedigos, Ori Ram, Yoel Zeldes, Daniel Jannai, Dor Muhlgay, Yoni Osin, Opher Lieber, Barak Lenz, Shai Shalev-Shwartz, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
Standing on the Shoulders of Giant Frozen Language Models. CoRR abs/2204.10019 (2022) - [i12]Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, Moshe Tennenholtz:
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. CoRR abs/2205.00445 (2022) - [i11]Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
Parallel Context Windows Improve In-Context Learning of Large Language Models. CoRR abs/2212.10947 (2022) - 2021
- [i10]Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua:
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. CoRR abs/2105.03928 (2021) - [i9]Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua:
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. CoRR abs/2110.04541 (2021) - 2020
- [i8]Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua:
Limits to Depth Efficiencies of Self-Attention. CoRR abs/2006.12467 (2020) - [i7]Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham:
PMI-Masking: Principled masking of correlated spans. CoRR abs/2010.01825 (2020) - 2019
- [i6]Or Sharir, Yoav Levine, Noam Wies, Giuseppe Carleo, Amnon Shashua:
Deep autoregressive models for the efficient variational simulation of many-body quantum systems. CoRR abs/1902.04057 (2019) - [i5]Yoav Levine, Barak Lenz, Or Dagan, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham:
SenseBERT: Driving Some Sense into BERT. CoRR abs/1908.05646 (2019) - 2018
- [i4]Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua:
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks. CoRR abs/1803.09780 (2018) - 2017
- [i3]Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua:
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. CoRR abs/1704.01552 (2017) - [i2]Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua:
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions. CoRR abs/1705.02302 (2017) - [i1]Yoav Levine, Or Sharir, Amnon Shashua:
Benefits of Depth for Long-Term Memory of Recurrent Networks. CoRR abs/1710.09431 (2017)
Coauthor Index
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