Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning. - David Mascharka; Philip Tran; Ryan Soklaski; Arjun Majumdar (CVPR, 2018)

Tools and Practices for Responsible AI Engineering. - Ryan Soklaski; Justin Goodwin; Olivia M. Brown; Michael Yee; Jason Matterer (CoRR, 2022)

Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration. - Ryan Soklaski; Michael Yee; Theodoros Tsiligkaridis (CoRR, 2022)

Neural scaling of deep chemical models. - Nathan C. Frey; Ryan Soklaski; Simon Axelrod; Siddharth Samsi; Rafael Gómez-Bombarelli; Connor W. Coley; Vijay Gadepally (Nat. Mac. Intell., 2023)

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. - Carson Denison; Monte MacDiarmid; Fazl Barez; David Duvenaud; Shauna Kravec; Samuel Marks; Nicholas Schiefer; Ryan Soklaski; Alex Tamkin; Jared Kaplan; Buck Shlegeris; Samuel R. Bowman; et al. (CoRR, 2024)