David Brandfonbrener

44 papers A* 14A 1Journal 28

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interleaved Head Attention. CoRR Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal, Rishabh Tiwari, Devvrit Khatri, David Brandfonbrener, Paul Pu Liang, Inderjit S. Dhillon, Manzil Zaheer
2025	A*	`conf`	Deconstructing What Makes a Good Optimizer for Autoregressive Language Models. ICLR Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade
2025	J	`jnl`	GQ-VAE: A gated quantized VAE for learning variable length tokens. CoRR Theo Datta, Kayla Huang, Sham M. Kakade, David Brandfonbrener
2025	J	`jnl`	Generalized Parallel Scaling with Interdependent Generations. CoRR Harry Dong, David Brandfonbrener, Eryk Helenowski, Yun He, Mrinal Kumar, Han Fang, Yuejie Chi, Karthik Abinav Sankararaman
2025	J	`jnl`	Let's (not) just put things in Context: Test-Time Training for Long-Context LLMs. CoRR Rachit Bansal, Aston Zhang, Rishabh Tiwari, Lovish Madaan, Sai Surya Duvvuri, Devvrit Khatri, David Brandfonbrener, David Alvarez-Melis, Prajjwal Bhargava, Mihir Sanjay Kale, Samy Jelassi
2025	J	`jnl`	Loss-to-Loss Prediction: Scaling Laws for All Datasets. Trans. Mach. Learn. Res. David Brandfonbrener, Nikhil Anand, Nikhil Vyas, Eran Malach, Sham M. Kakade
2025	A*	`conf`	Mixture of Parrots: Experts improve memorization more than reasoning. ICLR Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach
2025	A*	`conf`	SOAP: Improving and Stabilizing Shampoo using Adam for Language Modeling. ICLR Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade
2025	J	`jnl`	The Art of Scaling Reinforcement Learning Compute for LLMs. CoRR Devvrit Khatri, Lovish Madaan, Rishabh Tiwari, Rachit Bansal, Sai Surya Duvvuri, Manzil Zaheer, Inderjit S. Dhillon, David Brandfonbrener, Rishabh Agarwal
2025	A*	`conf`	The Role of Sparsity for Length Generalization in LLMs. ICML Noah Golowich, Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach
2025	J	`jnl`	The Role of Sparsity for Length Generalization in Transformers. CoRR Noah Golowich, Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach
2025	A*	`conf`	Universal Length Generalization with Turing Programs. ICML Kaiying Hou, David Brandfonbrener, Sham M. Kakade, Samy Jelassi, Eran Malach
2024	A*	`conf`	CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training. NeurIPS David Brandfonbrener, Hanlin Zhang, Andreas Kirsch, Jonathan Richard Schwarz, Sham M. Kakade
2024	J	`jnl`	CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training. CoRR David Brandfonbrener, Hanlin Zhang, Andreas Kirsch, Jonathan Richard Schwarz, Sham M. Kakade
2024	J	`jnl`	Deconstructing What Makes a Good Optimizer for Language Models. CoRR Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade
2024	J	`jnl`	Loss-to-Loss Prediction: Scaling Laws for All Datasets. CoRR David Brandfonbrener, Nikhil Anand, Nikhil Vyas, Eran Malach, Sham M. Kakade
2024	J	`jnl`	Mixture of Parrots: Experts improve memorization more than reasoning. CoRR Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach
2024	A*	`conf`	Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. ICML Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener
2024	J	`jnl`	Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. CoRR Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener
2024	A*	`conf`	Repeat After Me: Transformers are Better than State Space Models at Copying. ICML Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach
2024	J	`jnl`	Repeat After Me: Transformers are Better than State Space Models at Copying. CoRR Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach
2024	J	`jnl`	SOAP: Improving and Stabilizing Shampoo using Adam. CoRR Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade
2024	J	`jnl`	Universal Length Generalization with Turing Programs. CoRR Kaiying Hou, David Brandfonbrener, Sham M. Kakade, Samy Jelassi, Eran Malach
2024	J	`jnl`	Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search. CoRR David Brandfonbrener, Sibi Raja, Tarun Prasad, Chloe Loughridge, Jianang Yang, Simon Henniger, William E. Byrd, Robert Zinkov, Nada Amin
2023	—	`—`	Bridging the Gap from Supervised Learning to Control David Brandfonbrener
2023	A*	`conf`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. NeurIPS David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	J	`jnl`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. CoRR David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	A*	`conf`	Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. ICRA David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
2022	J	`jnl`	Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
2022	J	`jnl`	Incorporating Explicit Uncertainty Estimates into Deep Offline Reinforcement Learning. CoRR David Brandfonbrener, Remi Tachet des Combes, Romain Laroche
2022	J	`jnl`	Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. CoRR David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
2022	A*	`conf`	When does return-conditioned supervised learning work for offline reinforcement learning? NeurIPS David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
2022	J	`jnl`	When does return-conditioned supervised learning work for offline reinforcement learning? CoRR David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
2021	A*	`conf`	Offline Contextual Bandits with Overparameterized Models. ICML David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2021	A*	`conf`	Offline RL Without Off-Policy Evaluation. NeurIPS David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
2021	J	`jnl`	Offline RL Without Off-Policy Evaluation. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2021	J	`jnl`	Quantile Filtered Imitation Learning. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2020	J	`jnl`	Evaluating representations by the complexity of learning low-loss predictors. CoRR William F. Whitney, Min Jae Song, David Brandfonbrener, Jaan Altosaar, Kyunghyun Cho
2020	A	`conf`	Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. AISTATS Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric
2020	A*	`conf`	Geometric Insights into the Convergence of Nonlinear TD Learning. ICLR David Brandfonbrener, Joan Bruna
2020	J	`jnl`	Overfitting and Optimization in Offline Policy Learning. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2019	J	`jnl`	Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. CoRR Andrea Zanette, David Brandfonbrener, Matteo Pirotta, Alessandro Lazaric
2019	J	`jnl`	On the Expected Dynamics of Nonlinear TD Learning. CoRR David Brandfonbrener, Joan Bruna
2018	J	`jnl`	Two-Vertex Generators of Jacobians of Graphs. Electron. J. Comb. David Brandfonbrener, Pat Devlin, Netanel Friedenberg, Yuxuan Ke, Steffen Marcus, Henry Reichard, Ethan Sciamma