Physical principles for scalable neural recording. - Adam H. Marblestone; Bradley M. Zamft; Yael Maguire; Mikhail G. Shapiro; Thaddeus Cybulski; Joshua I. Glaser; Dario Amodei; P. Benjamin Stranges; Reza Kalhor; David Dalrymple; Dongjin Seo; Elad Alon; et al. (Frontiers Comput. Neurosci., 2013)

Searching for Collective Behavior in a Large Network of Sensory Neurons. - Gasper Tkacik; Olivier Marre; Dario Amodei; Elad Schneidman; William Bialek; Michael J. Berry II (PLoS Comput. Biol., 2014)

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Rishita Anubhai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; Erich Elsen; Jesse H. Engel; et al. (CoRR, 2015)

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Sundaram Ananthanarayanan; Rishita Anubhai; Jingliang Bai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; et al. (ICML, 2016)

Concrete Problems in AI Safety. - Dario Amodei; Chris Olah; Jacob Steinhardt; Paul F. Christiano; John Schulman; Dan Mané (CoRR, 2016)

Learning a Natural Language Interface with Neural Programmer. - Arvind Neelakantan; Quoc V. Le; Martín Abadi; Andrew McCallum; Dario Amodei (ICLR (Poster), 2017)

Deep Reinforcement Learning from Human Preferences. - Paul F. Christiano; Jan Leike; Tom B. Brown; Miljan Martic; Shane Legg; Dario Amodei (NIPS, 2017)

Reward learning from human preferences and demonstrations in Atari. - Borja Ibarz; Jan Leike; Tobias Pohlen; Geoffrey Irving; Shane Legg; Dario Amodei (NeurIPS, 2018)

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. - Miles Brundage; Shahar Avin; Jack Clark; Helen Toner; Peter Eckersley; Ben Garfinkel; Allan Dafoe; Paul Scharre; Thomas Zeitzoff; Bobby Filar; Hyrum S. Anderson; Heather Roff; et al. (CoRR, 2018)

AI safety via debate. - Geoffrey Irving; Paul F. Christiano; Dario Amodei (CoRR, 2018)

Variational Option Discovery Algorithms. - Joshua Achiam; Harrison Edwards; Dario Amodei; Pieter Abbeel (CoRR, 2018)

Supervising strong learners by amplifying weak experts. - Paul F. Christiano; Buck Shlegeris; Dario Amodei (CoRR, 2018)

An Empirical Model of Large-Batch Training. - Sam McCandlish; Jared Kaplan; Dario Amodei; OpenAI Dota Team (CoRR, 2018)

Fine-Tuning Language Models from Human Preferences. - Daniel M. Ziegler; Nisan Stiennon; Jeffrey Wu 003; Tom B. Brown; Alec Radford; Dario Amodei; Paul F. Christiano; Geoffrey Irving (CoRR, 2019)

Language Models are Few-Shot Learners. - Tom B. Brown; Benjamin Mann; Nick Ryder; Melanie Subbiah; Jared Kaplan; Prafulla Dhariwal; Arvind Neelakantan; Pranav Shyam; Girish Sastry; Amanda Askell; Sandhini Agarwal; Ariel Herbert-Voss; et al. (NeurIPS, 2020)

Learning to summarize with human feedback. - Nisan Stiennon; Long Ouyang; Jeffrey Wu 003; Daniel M. Ziegler; Ryan Lowe; Chelsea Voss; Alec Radford; Dario Amodei; Paul F. Christiano (NeurIPS, 2020)

Scaling Laws for Neural Language Models. - Jared Kaplan; Sam McCandlish; Tom Henighan; Tom B. Brown; Benjamin Chess; Rewon Child; Scott Gray; Alec Radford; Jeffrey Wu 003; Dario Amodei (CoRR, 2020)

Learning to summarize from human feedback. - Nisan Stiennon; Long Ouyang; Jeff Wu 003; Daniel M. Ziegler; Ryan Lowe; Chelsea Voss; Alec Radford; Dario Amodei; Paul F. Christiano (CoRR, 2020)

Scaling Laws for Autoregressive Generative Modeling. - Tom Henighan; Jared Kaplan; Mor Katz; Mark Chen 003; Christopher Hesse; Jacob Jackson; Heewoo Jun; Tom B. Brown; Prafulla Dhariwal; Scott Gray; Chris Hallacy; Benjamin Mann; et al. (CoRR, 2020)

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)

Toy Models of Superposition. - Nelson Elhage; Tristan Hume; Catherine Olsson; Nicholas Schiefer; Tom Henighan; Shauna Kravec; Zac Hatfield-Dodds; Robert Lasenby; Dawn Drain; Carol Chen; Roger B. Grosse; Sam McCandlish; 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)

Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. - Kunal Handa; Alex Tamkin; Miles McCain; Saffron Huang; Esin Durmus; Sarah Heck; Jared Mueller; Jerry Hong; Stuart Ritchie; Tim Belonax; Kevin K. Troy; Dario Amodei; et al. (CoRR, 2025)