A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. - Joshua Saxe; Richard E. Harang; Cody Wild; Hillary Sanders (IEEE Symposium on Security and Privacy Workshops, 2018)

ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation. - Ethan M. Rudd; Felipe N. Ducau; Cody Wild; Konstantin Berlin; Richard E. Harang (USENIX Security Symposium, 2019)

Adversarial Policies: Attacking Deep Reinforcement Learning. - Adam Gleave; Michael Dennis 001; Cody Wild; Neel Kant; Sergey Levine; Stuart Russell 001 (ICLR, 2020)

Neural Networks are Surprisingly Modular. - Daniel Filan; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2020)

An Empirical Investigation of Representation Learning for Imitation. - Cynthia Chen; Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; et al. (NeurIPS Datasets and Benchmarks, 2021)

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. - 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; et al. (NeurIPS (Competition and Demos), 2021)

Clusterability in Neural Networks. - Daniel Filan; Stephen Casper; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

The MineRL BASALT Competition on Learning from Human Feedback. - 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 001; et al. (CoRR, 2021)

Detecting Modularity in Deep Neural Networks. - Shlomi Hod; Stephen Casper; Daniel Filan; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. - 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; et al. (CoRR, 2022)

An Empirical Investigation of Representation Learning for Imitation. - Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; Rohin Shah (CoRR, 2022)

Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers. - Cody Wild; Jesper Anderson (CoRR, 2024)

On the generalization of language models from in-context learning and finetuning: a controlled study. - Andrew K. Lampinen; Arslan Chaudhry; Stephanie C. Y. Chan; Cody Wild; Diane Wan; Alex Ku; Jörg Bornschein; Razvan Pascanu; Murray Shanahan; James L. McClelland (CoRR, 2025)