Yoav Levine - RankMe

39 papers A* 9Journal 25Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming. CoRR 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, Amnon Shashua
2025	—	`conf`	Position: Language model developers should report train-test overlap. ICML (Position Papers) Andy K. Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang, Rishi Bommasani, Percy Liang
2024	J	`jnl`	Artificial Expert Intelligence through PAC-reasoning. CoRR Shai Shalev-Shwartz, Amnon Shashua, Gal Beniamini, Yoav Levine, Or Sharir, Noam Wies, Ido Ben-Shaul, Tomer Nussbaum, Shir Granot Peled
2024	A*	`conf`	Fundamental Limitations of Alignment in Large Language Models. ICML Yotam Wolf, Noam Wies, Oshri Avnery, Yoav Levine, Amnon Shashua
2024	—	`conf`	Generating Benchmarks for Factuality Evaluation of Language Models. EACL (1) Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
2024	J	`jnl`	Language model developers should report train-test overlap. CoRR Andy K. Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang, Rishi Bommasani, Percy Liang
2024	J	`jnl`	Rationality Report Cards: Assessing the Economic Rationality of Large Language Models. CoRR Narun K. Raman, Taylor Lundy, Samuel Joseph Amouyal, Yoav Levine, Kevin Leyton-Brown, Moshe Tennenholtz
2024	A*	`conf`	STEER: Assessing the Economic Rationality of Large Language Models. ICML Narun Krishnamurthi Raman, Taylor Lundy, Samuel Joseph Amouyal, Yoav Levine, Kevin Leyton-Brown, Moshe Tennenholtz
2024	J	`jnl`	Tradeoffs Between Alignment and Helpfulness in Language Models. CoRR Yotam Wolf, Noam Wies, Dorin Shteyman, Binyamin Rothberg, Yoav Levine, Amnon Shashua
2023	J	`jnl`	Fundamental Limitations of Alignment in Large Language Models. CoRR Yotam Wolf, Noam Wies, Yoav Levine, Amnon Shashua
2023	J	`jnl`	Generating Benchmarks for Factuality Evaluation of Language Models. CoRR Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham
2023	J	`jnl`	Human or Not? A Gamified Approach to the Turing Test. CoRR Daniel Jannai, Amos Meron, Barak Lenz, Yoav Levine, Yoav Shoham
2023	J	`jnl`	In-Context Retrieval-Augmented Language Models. CoRR Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
2023	J	`jnl`	In-Context Retrieval-Augmented Language Models. Trans. Assoc. Comput. Linguistics Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
2023	—	`conf`	Parallel Context Windows for Large Language Models. ACL (1) Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
2023	A*	`conf`	Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. ICLR Noam Wies, Yoav Levine, Amnon Shashua
2023	A*	`conf`	The Learnability of In-Context Learning. NeurIPS Noam Wies, Yoav Levine, Amnon Shashua
2023	J	`jnl`	The Learnability of In-Context Learning. CoRR Noam Wies, Yoav Levine, Amnon Shashua
2022	J	`jnl`	MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. CoRR 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
2022	J	`jnl`	Parallel Context Windows Improve In-Context Learning of Large Language Models. CoRR Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham
2022	J	`jnl`	Standing on the Shoulders of Giant Frozen Language Models. CoRR 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
2022	J	`jnl`	Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks. CoRR Noam Wies, Yoav Levine, Amnon Shashua
2022	A*	`conf`	The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. ICLR Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
2021	A*	`conf`	PMI-Masking: Principled masking of correlated spans. ICLR Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham
2021	J	`jnl`	The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. CoRR Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
2021	A*	`conf`	Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. ICML Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
2021	J	`jnl`	Which transformer architecture fits my data? A vocabulary bottleneck in self-attention. CoRR Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
2020	A*	`conf`	Limits to Depth Efficiencies of Self-Attention. NeurIPS Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua
2020	J	`jnl`	Limits to Depth Efficiencies of Self-Attention. CoRR Yoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua
2020	J	`jnl`	PMI-Masking: Principled masking of correlated spans. CoRR Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham
2020	A*	`conf`	SenseBERT: Driving Some Sense into BERT. ACL Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
2019	J	`jnl`	Deep autoregressive models for the efficient variational simulation of many-body quantum systems. CoRR Or Sharir, Yoav Levine, Noam Wies, Giuseppe Carleo, Amnon Shashua
2019	J	`jnl`	SenseBERT: Driving Some Sense into BERT. CoRR Yoav Levine, Barak Lenz, Or Dagan, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
2018	—	`conf`	Benefits of Depth for Long-Term Memory of Recurrent Networks. ICLR (Workshop) Yoav Levine, Or Sharir, Amnon Shashua
2018	J	`jnl`	Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks. CoRR Yoav Levine, Or Sharir, Nadav Cohen, Amnon Shashua
2018	—	`conf`	Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. ICLR (Poster) Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua
2017	J	`jnl`	Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions. CoRR Nadav Cohen, Or Sharir, Yoav Levine, Ronen Tamari, David Yakira, Amnon Shashua
2017	J	`jnl`	Benefits of Depth for Long-Term Memory of Recurrent Networks. CoRR Yoav Levine, Or Sharir, Amnon Shashua
2017	J	`jnl`	Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design. CoRR Yoav Levine, David Yakira, Nadav Cohen, Amnon Shashua