Ethan Perez
As of October 2026, Ethan Perez leads the alignment team at Anthropic, where he hopes to reduce existential risks from AI systems. He studied natural language processing at New York University, advised by Kyunghyun Cho and Douwe Kiela. He co-authored retrieval-augmented generation work in 2020, scalable oversight and red teaming papers in 2022, and Sleeper Agents in 2024. The debate paper Debating with More Persuasive LLMs Leads to More Truthful Answers received an ICML 2024 Best Paper award.
Timeline
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2020
A retrieval-augmented generation paper
He co-authors the 2020 NeurIPS paper Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, which combines parametric and non-parametric memory.
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April 2022
Joining Anthropic after the PhD
In April 2022, he gives an NLP seminar talk as a final-year Ph.D. student in natural language processing at New York University, advised by Kyunghyun Cho and Douwe Kiela. He is set to join Anthropic as a Research Scientist after graduation.
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2022
Measuring progress on scalable oversight
He co-authors Measuring Progress on Scalable Oversight for Large Language Models in 2022, a study finding that human participants who chat with an unreliable language model assistant outperform the model alone.
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2022
Red teaming language models
He co-authors Red Teaming Language Models to Reduce Harms in 2022, a paper describing early efforts to find and reduce harmful model outputs.
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2024
The Sleeper Agents paper
In 2024, he co-authors Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training, which builds proof-of-concept examples of deceptive behavior in large language models.
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2024
A best paper at ICML
His debate paper, Debating with More Persuasive LLMs Leads to More Truthful Answers, receives an ICML 2024 Best Paper award.
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As of October 2026
Head of alignment at Anthropic
As of October 2026, he leads the alignment team at Anthropic as its Head of Alignment, where he hopes to reduce existential risks from AI systems.
Sources and credits
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