Cody Wild - RankMe

16 papers A* 2Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	On the generalization of language models from in-context learning and finetuning: a controlled study. CoRR Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland
2024	J	`jnl`	Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers. CoRR Cody Wild, Jesper Anderson
2022	J	`jnl`	An Empirical Investigation of Representation Learning for Imitation. CoRR Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2022	J	`jnl`	Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum
2021	—	`conf`	An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2021	J	`jnl`	Clusterability in Neural Networks. CoRR Daniel Filan, Stephen Casper, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell
2021	J	`jnl`	Detecting Modularity in Deep Neural Networks. CoRR Shlomi Hod, Stephen Casper, Daniel Filan, Cody Wild, Andrew Critch, Stuart Russell
2021	—	`conf`	Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum
2021	J	`jnl`	The MineRL BASALT Competition on Learning from Human Feedback. CoRR Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan
2020	A*	`conf`	Adversarial Policies: Attacking Deep Reinforcement Learning. ICLR Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell
2020	J	`jnl`	Neural Networks are Surprisingly Modular. CoRR Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell
2019	A*	`conf`	ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation. USENIX Security Symposium Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard E. Harang
2019	J	`jnl`	ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation. CoRR Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard E. Harang
2019	J	`jnl`	Adversarial Policies: Attacking Deep Reinforcement Learning. CoRR Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, Stuart Russell
2018	—	`conf`	A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. IEEE Symposium on Security and Privacy Workshops Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders
2018	J	`jnl`	A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. CoRR Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders