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2020 – today
- 2024
[i4]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, Ethan Perez, Evan Hubinger:
Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. CoRR abs/2406.10162 (2024)- 2023
- [j1]Nathan C. Frey
, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally:
Neural scaling of deep chemical models. Nat. Mac. Intell. 5(11): 1297-1305 (2023) - 2022
- [i3]Ryan Soklaski, Justin Goodwin, Olivia M. Brown, Michael Yee, Jason Matterer:
Tools and Practices for Responsible AI Engineering. CoRR abs/2201.05647 (2022) - [i2]Ryan Soklaski, Michael Yee, Theodoros Tsiligkaridis:
Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration. CoRR abs/2202.12412 (2022)
2010 – 2019
- 2018
- [c1]David Mascharka, Philip Tran, Ryan Soklaski, Arjun Majumdar:
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning. CVPR 2018: 4942-4950 - [i1]David Mascharka, Philip Tran, Ryan Soklaski, Arjun Majumdar:
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning. CoRR abs/1803.05268 (2018)
Coauthor Index
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