Ethan Perez

Research Scientist | Anthropic

Ethan previously collaborated with FAR.AI and is a Research Scientist at Anthropic. He completed his Ph.D. in Natural Language Processing at New York University. He was advised by Kyunghyun Cho and Douwe Kiela and funded by NSF and Open Philanthropy. His research focuses on aligning language models with human preferences, e.g., for content that is helpful, honest, and harmless. In particular, he is excited about developing learning algorithms that outdo humans at generating such content, by producing text that is free of social biases, cognitive biases, common misconceptions, and other limitations. Previously, he has spent time at DeepMind, Facebook AI Research, Montreal Institute for Learning Algorithms, Uber, and Google. He earned a Bachelor’s from Rice University as the Engineering department’s Outstanding Senior. Visit his website to find out more.

NEWs & publications

VLM-RM: Specifying Rewards with Natural Language
October 19, 2023
vlm-rm-specifying-rewards-with-natural-language
Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning
vision-language-models-are-zero-shot-reward-models-for-reinforcement-learning
Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning
October 19, 2023
vision-language-models-are-zero-shot-reward-models-for-reinforcement-learning
VLM-RM: Specifying Rewards with Natural Language
vlm-rm-specifying-rewards-with-natural-language
Inverse Scaling: When Bigger Isn't Better
June 15, 2023
inverse-scaling-when-bigger-isnt-better
Improving Code Generation by Training with Natural Language Feedback
March 28, 2023
improving-code-generation-by-training-with-natural-language-feedback
Training Language Models with Language Feedback at Scale
March 28, 2023
training-language-models-with-language-feedback-at-scale
Few-shot Adaptation Works with UnpredicTable Data
August 8, 2022
few-shot-adaptation-works-with-unpredictable-data
Training Language Models with Language Feedback
November 17, 2022
training-language-models-with-language-feedback
Pretraining Language Models with Human Preferences
February 16, 2023
pretraining-language-models-with-human-preferences
RL with KL penalties is better viewed as Bayesian inference
August 8, 2022
rl-with-kl-penalties-is-better-viewed-as-bayesian-inference