Tom B. Brown

According to our database1, Tom B. Brown authored at least 16 papers between 2017 and 2022.

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Bibliography

2022
Scaling Laws and Interpretability of Learning from Repeated Data.
CoRR, 2022

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.
CoRR, 2022

Predictability and Surprise in Large Generative Models.
CoRR, 2022


2021
A General Language Assistant as a Laboratory for Alignment.
CoRR, 2021

Extracting Training Data from Large Language Models.
Proceedings of the 30th USENIX Security Symposium, 2021

2020
Scaling Laws for Autoregressive Generative Modeling.
CoRR, 2020

Measuring the Algorithmic Efficiency of Neural Networks.
CoRR, 2020

Scaling Laws for Neural Language Models.
CoRR, 2020


2019
Fine-Tuning Language Models from Human Preferences.
CoRR, 2019

2018
Unrestricted Adversarial Examples.
CoRR, 2018

Skill Rating for Generative Models.
CoRR, 2018

Is Generator Conditioning Causally Related to GAN Performance?
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Adversarial Patch.
CoRR, 2017

Deep Reinforcement Learning from Human Preferences.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017


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