Etai Littwin - RankMe

48 papers A* 16A 2B 1Journal 29

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Distillation Scaling Laws. ICML Dan Busbridge, Amitis Shidani, Floris Weers, Jason Ramapuram, Etai Littwin, Russell Webb
2025	J	`jnl`	Distillation Scaling Laws. CoRR Dan Busbridge, Amitis Shidani, Floris Weers, Jason Ramapuram, Etai Littwin, Russ Webb
2025	J	`jnl`	Rethinking JEPA: Compute-Efficient Video SSL with Frozen Teachers. CoRR Xianhang Li, Chen Huang, Chun-Liang Li, Eran Malach, Josh M. Susskind, Vimal Thilak, Etai Littwin
2025	J	`jnl`	To Infinity and Beyond: Tool-Use Unlocks Length Generalization in State Space Models. CoRR Eran Malach, Omid Saremi, Sinead Williamson, Arwen Bradley, Aryo Lotfi, Emmanuel Abbe, Joshua M. Susskind, Etai Littwin
2025	A	`conf`	UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity. UMAP Yicheng Fu, Raviteja Anantha, Prabal Vashisht, Jianpeng Cheng, Etai Littwin
2024	J	`jnl`	Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning. CoRR Etai Littwin, Vimal Thilak, Anand Gopalakrishnan
2024	A*	`conf`	How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. NeurIPS Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind
2024	J	`jnl`	How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. CoRR Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind
2024	A*	`conf`	LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. ICLR Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2024	J	`jnl`	The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods. Trans. Mach. Learn. Res. Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind
2024	J	`jnl`	UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity. CoRR Yicheng Fu, Raviteja Anantha, Prabal Vashisht, Jianpeng Cheng, Etai Littwin
2024	A*	`conf`	Vanishing Gradients in Reinforcement Finetuning of Language Models. ICLR Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2024	A*	`conf`	What Algorithms can Transformers Learn? A Study in Length Generalization. ICLR Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran
2024	A*	`conf`	When can transformers reason with abstract symbols? ICLR Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind
2023	A*	`conf`	Adaptive Optimization in the ∞-Width Limit. ICLR Etai Littwin, Greg Yang
2023	J	`jnl`	Adaptivity and Modularity for Efficient Generalization Over Task Complexity. CoRR Samira Abnar, Omid Saremi, Laurent Dinh, Shantel Wilson, Miguel Ángel Bautista, Chen Huang, Vimal Thilak, Etai Littwin, Jiatao Gu, Josh M. Susskind, Samy Bengio
2023	J	`jnl`	LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. CoRR Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2023	A*	`conf`	Stabilizing Transformer Training by Preventing Attention Entropy Collapse. ICML Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind
2023	J	`jnl`	Stabilizing Transformer Training by Preventing Attention Entropy Collapse. CoRR Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind
2023	J	`jnl`	Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit. CoRR Greg Yang, Etai Littwin
2023	J	`jnl`	The NTK approximation is valid for longer than you think. CoRR Enric Boix-Adserà, Etai Littwin
2023	J	`jnl`	Tight conditions for when the NTK approximation is valid. Trans. Mach. Learn. Res. Enric Boix-Adserà, Etai Littwin
2023	A*	`conf`	Transformers learn through gradual rank increase. NeurIPS Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind
2023	J	`jnl`	Transformers learn through gradual rank increase. CoRR Enric Boix-Adserà, Etai Littwin, Emmanuel Abbe, Samy Bengio, Joshua M. Susskind
2023	J	`jnl`	Vanishing Gradients in Reinforcement Finetuning of Language Models. CoRR Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2023	J	`jnl`	What Algorithms can Transformers Learn? A Study in Length Generalization. CoRR Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Josh M. Susskind, Samy Bengio, Preetum Nakkiran
2023	J	`jnl`	When can transformers reason with abstract symbols? CoRR Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind
2022	A*	`conf`	Learning Representation from Neural Fisher Kernel with Low-rank Approximation. ICLR Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind
2022	J	`jnl`	Learning Representation from Neural Fisher Kernel with Low-rank Approximation. CoRR Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Josh M. Susskind
2022	J	`jnl`	The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon. CoRR Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind
2021	J	`jnl`	Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. CoRR Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang
2021	J	`jnl`	Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks. CoRR Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua M. Susskind
2021	A	`conf`	On random kernels of residual architectures. UAI Etai Littwin, Tomer Galanti, Lior Wolf
2021	A*	`conf`	Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics. ICML Greg Yang, Etai Littwin
2021	J	`jnl`	Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics. CoRR Greg Yang, Etai Littwin
2020	A*	`conf`	Collegial Ensembles. NeurIPS Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan
2020	J	`jnl`	Collegial Ensembles. CoRR Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan
2020	A*	`conf`	On Infinite-Width Hypernetworks. NeurIPS Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang
2020	J	`jnl`	On the Convex Behavior of Deep Neural Networks in Relation to the Layers' Width. CoRR Etai Littwin, Lior Wolf
2020	J	`jnl`	On the Optimization Dynamics of Wide Hypernetworks. CoRR Etai Littwin, Tomer Galanti, Lior Wolf
2020	J	`jnl`	Residual Tangent Kernels. CoRR Etai Littwin, Lior Wolf
2018	A*	`conf`	Regularizing by the Variance of the Activations' Sample-Variances. NeurIPS Etai Littwin, Lior Wolf
2018	J	`jnl`	Regularizing by the Variance of the Activations' Sample-Variances. CoRR Etai Littwin, Lior Wolf
2016	B	`conf`	Complexity of multiverse networks and their multilayer generalization. ICPR Etai Littwin, Lior Wolf
2016	J	`jnl`	The Loss Surface of Residual Networks: Ensembles and the Role of Batch Normalization. CoRR Etai Littwin, Lior Wolf
2016	A*	`conf`	The Multiverse Loss for Robust Transfer Learning. CVPR Etai Littwin, Lior Wolf
2015	A*	`conf`	Spherical embedding of inlier silhouette dissimilarities. CVPR Etai Littwin, Hadar Averbuch-Elor, Daniel Cohen-Or
2015	J	`jnl`	The Multiverse Loss for Robust Transfer Learning. CoRR Etai Littwin, Lior Wolf