Evaluating Large Language Models Trained on Code. - Mark Chen 003; Jerry Tworek; Heewoo Jun; Qiming Yuan; Henrique Pondé de Oliveira Pinto; Jared Kaplan; Harri Edwards; Yuri Burda; Nicholas Joseph; Greg Brockman; Alex Ray; Raul Puri; et al. (CoRR, 2021)

A General Language Assistant as a Laboratory for Alignment. - Amanda Askell; Yuntao Bai; Anna Chen; Dawn Drain; Deep Ganguli; Tom Henighan; Andy Jones; Nicholas Joseph; Benjamin Mann; Nova DasSarma; Nelson Elhage; Zac Hatfield-Dodds; et al. (CoRR, 2021)

Predictability and Surprise in Large Generative Models. - Deep Ganguli; Danny Hernandez; Liane Lovitt; Amanda Askell; Yuntao Bai; Anna Chen; Tom Conerly; Nova DasSarma; Dawn Drain; Nelson Elhage; Sheer El Showk; Stanislav Fort; et al. (FAccT, 2022)

Predictability and Surprise in Large Generative Models. - Deep Ganguli; Danny Hernandez; Liane Lovitt; Nova DasSarma; Tom Henighan; Andy Jones; Nicholas Joseph; Jackson Kernion; Benjamin Mann; Amanda Askell; Yuntao Bai; Anna Chen; et al. (CoRR, 2022)

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)

Scaling Laws and Interpretability of Learning from Repeated Data. - Danny Hernandez; Tom B. Brown; Tom Conerly; Nova DasSarma; Dawn Drain; Sheer El Showk; Nelson Elhage; Zac Hatfield-Dodds; Tom Henighan; Tristan Hume; Scott Johnston; Benjamin Mann; 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)

In-context Learning and Induction Heads. - Catherine Olsson; Nelson Elhage; Neel Nanda; Nicholas Joseph; Nova DasSarma; Tom Henighan; Ben Mann; Amanda Askell; Yuntao Bai; Anna Chen; Tom Conerly; Dawn Drain; et al. (CoRR, 2022)

Measuring Progress on Scalable Oversight for Large Language Models. - Samuel R. Bowman; Jeeyoon Hyun; Ethan Perez; Edwin Chen; Craig Pettit; Scott Heiner; Kamile Lukosiute; Amanda Askell; Andy Jones; Anna Chen; Anna Goldie; Azalia Mirhoseini; et al. (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)

Towards Measuring the Representation of Subjective Global Opinions in Language Models. - Esin Durmus; Karina Nyugen; Thomas I. Liao; Nicholas Schiefer; Amanda Askell; Anton Bakhtin; Carol Chen; Zac Hatfield-Dodds; Danny Hernandez; Nicholas Joseph; Liane Lovitt; Sam McCandlish; et al. (CoRR, 2023)

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning. - Ansh Radhakrishnan; Karina Nguyen; Anna Chen; Carol Chen; Carson Denison; Danny Hernandez; Esin Durmus; Evan Hubinger; Jackson Kernion; Kamile Lukosiute; Newton Cheng; Nicholas Joseph; 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)

Studying Large Language Model Generalization with Influence Functions. - Roger B. Grosse; Juhan Bae; Cem Anil; Nelson Elhage; Alex Tamkin; Amirhossein Tajdini; Benoit Steiner; Dustin Li; Esin Durmus; Ethan Perez; Evan Hubinger; Kamile Lukosiute; 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)

Evaluating and Mitigating Discrimination in Language Model Decisions. - Alex Tamkin; Amanda Askell; Liane Lovitt; Esin Durmus; Nicholas Joseph; Shauna Kravec; Karina Nguyen; Jared Kaplan; Deep Ganguli (CoRR, 2023)