Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty. - Dan Hendrycks; Mantas Mazeika; Saurav Kadavath; Dawn Song (NeurIPS, 2019)

The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization. - Dan Hendrycks; Steven Basart; Norman Mu; Saurav Kadavath; Frank Wang; Evan Dorundo; Rahul Desai; Tyler Zhu; Samyak Parajuli; Mike Guo; Dawn Song; Jacob Steinhardt; et al. (ICCV, 2021)

Measuring Mathematical Problem Solving With the MATH Dataset. - Dan Hendrycks; Collin Burns; Saurav Kadavath; Akul Arora; Steven Basart; Eric Tang; Dawn Song; Jacob Steinhardt (NeurIPS Datasets and Benchmarks, 2021)

Measuring Coding Challenge Competence With APPS. - Dan Hendrycks; Steven Basart; Saurav Kadavath; Mantas Mazeika; Akul Arora; Ethan Guo; Collin Burns; Samir Puranik; Horace He; Dawn Song; Jacob Steinhardt (NeurIPS Datasets and Benchmarks, 2021)

Pretraining & Reinforcement Learning: Sharpening the Axe Before Cutting the Tree. - Saurav Kadavath; Samuel Paradis; Brian Yao (CoRR, 2021)

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. - Yuntao Bai; Andy Jones; Kamal Ndousse; Amanda Askell; Anna Chen; Nova DasSarma; Dawn Drain; Stanislav Fort; Deep Ganguli; Tom Henighan; Nicholas Joseph; Saurav Kadavath; et al. (CoRR, 2022)

Language Models (Mostly) Know What They Know. - Saurav Kadavath; Tom Conerly; Amanda Askell; Tom Henighan; Dawn Drain; Ethan Perez; Nicholas Schiefer; Zac Hatfield-Dodds; Nova DasSarma; Eli Tran-Johnson; Scott Johnston; Sheer El Showk; et al. (CoRR, 2022)

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned. - Deep Ganguli; Liane Lovitt; Jackson Kernion; Amanda Askell; Yuntao Bai; Saurav Kadavath; Ben Mann; Ethan Perez; Nicholas Schiefer; Kamal Ndousse; Andy Jones; Sam Bowman 001; et al. (CoRR, 2022)

DeepChrome 2.0: Investigating and Improving Architectures, Visualizations, & Experiments. - Saurav Kadavath; Samuel Paradis; Jacob Yeung (CoRR, 2022)

Constitutional AI: Harmlessness from AI Feedback. - Yuntao Bai; Saurav Kadavath; Sandipan Kundu; Amanda Askell; Jackson Kernion; Andy Jones; Anna Chen; Anna Goldie; Azalia Mirhoseini; Cameron McKinnon; Carol Chen; Catherine Olsson; et al. (CoRR, 2022)

Discovering Language Model Behaviors with Model-Written Evaluations. - Ethan Perez; Sam Ringer; Kamile Lukosiute; Karina Nguyen; Edwin Chen; Scott Heiner; Craig Pettit; Catherine Olsson; Sandipan Kundu; Saurav Kadavath; Andy Jones; Anna Chen; et al. (CoRR, 2022)

Discovering Language Model Behaviors with Model-Written Evaluations. - Ethan Perez; Sam Ringer; Kamile Lukosiute; Karina Nguyen; Edwin Chen; Scott Heiner; Craig Pettit; Catherine Olsson; Sandipan Kundu; Saurav Kadavath; Andy Jones; Anna Chen; et al. (ACL (Findings), 2023)

The Capacity for Moral Self-Correction in Large Language Models. - Deep Ganguli; Amanda Askell; Nicholas Schiefer; Thomas I. Liao; Kamile Lukosiute; Anna Chen; Anna Goldie; Azalia Mirhoseini; Catherine Olsson; Danny Hernandez; Dawn Drain; Dustin Li; et al. (CoRR, 2023)

Measuring Faithfulness in Chain-of-Thought Reasoning. - Tamera Lanham; Anna Chen; Ansh Radhakrishnan; Benoit Steiner; Carson Denison; Danny Hernandez; Dustin Li; Esin Durmus; Evan Hubinger; Jackson Kernion; Kamile Lukosiute; Karina Nguyen; et al. (CoRR, 2023)

Specific versus General Principles for Constitutional AI. - Sandipan Kundu; Yuntao Bai; Saurav Kadavath; Amanda Askell; Andrew Callahan; Anna Chen; Anna Goldie; Avital Balwit; Azalia Mirhoseini; Brayden McLean; Catherine Olsson; Cassie Evraets; et al. (CoRR, 2023)