Brett W. Larsen

22 papers A* 4Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DatBench: Discriminative, Faithful, and Efficient VLM Evaluations. CoRR Siddharth Joshi, Haoli Yin, Rishabh Adiga, Ricardo Monti, Aldo Carranza, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Luke Merrick, Parth Doshi, Paul Burstein, Pratyush Maini, Scott Loftin, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2026	J	`jnl`	The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data. CoRR Christina Baek, Ricardo Pio Monti, David Schwab, Amro Abbas, Rishabh Adiga, Cody Blakeney, Maximilian Böther, Paul Burstein, Aldo Gael Carranza, Alvin Deng, Parth Doshi, Vineeth Dorna, Alex Fang, Tony Jiang, Siddharth Joshi, Brett W. Larsen, Jason Chan Lee, Katherine L. Mentzer, Luke Merrick, Haakon Mongstad, Fan Pan, Anshuman Suri, Darren Teh, Jason Telanoff, Jack Urbanek, Zhengping Wang, Josh Wills, Haoli Yin, Aditi Raghunathan, J. Zico Kolter, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt, Pratyush Maini
2026	J	`jnl`	ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset. CoRR Aldo Gael Carranza, Kaleigh Mentzer, Ricardo Pio Monti, Alex Fang, Alvin Deng, Amro Abbas, Anshuman Suri, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Diego Kiner, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Luke Merrick, Maximilian Böther, Parth Doshi, Paul Burstein, Pratyush Maini, Rishabh Adiga, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2025	J	`jnl`	BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining. CoRR Pratyush Maini, Vineeth Dorna, Parth Doshi, Aldo Carranza, Fan Pan, Jack Urbanek, Paul Burstein, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Charvi Bannur, Christina Baek, Darren Teh, David Schwab, Haakon Mongstad, Haoli Yin, Josh Wills, Kaleigh Mentzer, Luke Merrick, Ricardo Monti, Rishabh Adiga, Siddharth Joshi, Spandan Das, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2025	J	`jnl`	Luxical: High-Speed Lexical-Dense Text Embeddings. CoRR Luke Merrick, Alex Fang, Aldo Carranza, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Paul Burstein, Parth Doshi, Paul Burnstein, Pratyush Maini, Ricardo Monti, Rishabh Adiga, Scott Loftin, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2024	J	`jnl`	Does your data spark joy? Performance gains from domain upsampling at the end of training. CoRR Cody Blakeney, Mansheej Paul, Brett W. Larsen, Sean Owen, Jonathan Frankle
2024	A*	`conf`	Estimating Shape Distances on Neural Representations with Limited Samples. ICLR Dean A. Pospisil, Brett W. Larsen, Sarah E. Harvey, Alex H. Williams
2024	J	`jnl`	Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data. CoRR Brett W. Larsen, Tamara G. Kolda, Anru R. Zhang, Alex H. Williams
2023	—	`conf`	Duality of Bures and Shape Distances with Implications for Comparing Neural Representations. UniReps Sarah E. Harvey, Brett W. Larsen, Alex H. Williams
2023	J	`jnl`	Duality of Bures and Shape Distances with Implications for Comparing Neural Representations. CoRR Sarah E. Harvey, Brett W. Larsen, Alex H. Williams
2023	J	`jnl`	Estimating Shape Distances on Neural Representations with Limited Samples. CoRR Dean A. Pospisil, Brett W. Larsen, Sarah E. Harvey, Alex H. Williams
2023	A*	`conf`	Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? ICLR Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
2022	A*	`conf`	How many degrees of freedom do we need to train deep networks: a loss landscape perspective. ICLR Brett W. Larsen, Stanislav Fort, Nic Becker, Surya Ganguli
2022	A*	`conf`	Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. NeurIPS Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
2022	J	`jnl`	Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. CoRR Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
2022	J	`jnl`	Practical Leverage-Based Sampling for Low-Rank Tensor Decomposition. SIAM J. Matrix Anal. Appl. Brett W. Larsen, Tamara G. Kolda
2022	J	`jnl`	Sketching Matrix Least Squares via Leverage Scores Estimates. CoRR Brett W. Larsen, Tamara G. Kolda
2022	J	`jnl`	Towards a more general understanding of the algorithmic utility of recurrent connections. PLoS Comput. Biol. Brett W. Larsen, Shaul Druckmann
2022	J	`jnl`	Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? CoRR Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
2021	J	`jnl`	How many degrees of freedom do we need to train deep networks: a loss landscape perspective. CoRR Brett W. Larsen, Stanislav Fort, Nic Becker, Surya Ganguli
2020	J	`jnl`	No Spurious Local Minima in Deep Quadratic Networks. CoRR Abbas Kazemipour, Brett W. Larsen, Shaul Druckmann
2020	J	`jnl`	Practical Leverage-Based Sampling for Low-Rank Tensor Decomposition. CoRR Brett W. Larsen, Tamara G. Kolda