Christopher Hesse
Christopher Hesse is an OpenAI technical staff member whose AI work spans reinforcement learning, language models, code generation, and mathematical reasoning. His early OpenAI work included the Dota 2 study behind OpenAI Five and the Procgen benchmark. He co-authored papers on GPT-3 few-shot learning, Codex and HumanEval, verifiers for grade-school math, and WebGPT's browser-assisted answers with human feedback. He later co-authored OpenAI's GPT-4o and o1 system cards. As of October 2026, he is a Member of Technical Staff at OpenAI.
Timeline
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2019
OpenAI Five and Procgen
In 2019, he co-authors OpenAI's Dota 2 study, which describes OpenAI Five's win over world champion Team OG. Also in 2019, he co-authors Procgen Benchmark, a suite of 16 procedurally generated game-like environments for measuring sample efficiency and generalization in reinforcement learning.
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2020
GPT-3 few-shot learning
In 2020, he co-authors “Language Models are Few-Shot Learners,” which tests a 175-billion-parameter GPT-3 on tasks specified through text interaction and few-shot demonstrations.
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2021
Codex and HumanEval
In 2021, he co-authors the Codex study, which introduces HumanEval to measure functional correctness for programs synthesized from docstrings. OpenAI's repository provides an evaluation harness for the dataset.
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2021
Math verifiers and GSM8K
In 2021, he co-authors research that introduces GSM8K, a dataset of 8.5K grade-school math problems, and trains verifiers to rank candidate solutions.
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2021
WebGPT and human feedback
In 2021, he co-authors WebGPT, which fine-tunes GPT-3 to answer long-form questions in a text-based web-browsing environment and improves answer quality with human feedback.
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2024
GPT-4o system card
In 2024, he co-authors OpenAI's GPT-4o System Card, which details its capabilities, limitations, and safety evaluations across speech, text, and images.
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2024–2026
The o1 system card
In 2024, he co-authors OpenAI's o1 System Card, which outlines safety evaluations and external red teaming. The team revises the report in April 2026.
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Since 2016
OpenAI technical staff
As of October 2026, he is a Member of Technical Staff at OpenAI.
Sources and credits
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- Dota 2 with Large Scale Deep Reinforcement Learning
- Leveraging Procedural Generation to Benchmark Reinforcement Learning
- Language Models are Few-Shot Learners
- Evaluating Large Language Models Trained on Code
- GitHub - openai/human-eval: Code for the paper Evaluating Large Language Models Trained on Code
- Training Verifiers to Solve Math Word Problems
- WebGPT: Browser-assisted question-answering with human feedback
- GPT-4o System Card
- OpenAI o1 System Card
- Christopher Hesse | alphaXiv
