Tom B. Brown

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Google ∙ OpenAI

Scaling Laws for Autoregressive Generative Modeling

We identify empirical scaling laws for the cross-entropy loss in four do...
10/28/2020 ∙ by Tom Henighan, et al. ∙ 2 ∙ share

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Language Models are Few-Shot Learners

Recent work has demonstrated substantial gains on many NLP tasks and ben...
05/28/2020 ∙ by Tom B. Brown, et al. ∙ 33 ∙ share

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Measuring the Algorithmic Efficiency of Neural Networks

Three factors drive the advance of AI: algorithmic innovation, data, and...
05/08/2020 ∙ by Danny Hernandez, et al. ∙ 0 ∙ share

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Scaling Laws for Neural Language Models

We study empirical scaling laws for language model performance on the cr...
01/23/2020 ∙ by Jared Kaplan, et al. ∙ 0 ∙ share

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Fine-Tuning Language Models from Human Preferences

Reward learning enables the application of reinforcement learning (RL) t...
09/18/2019 ∙ by Daniel M. Ziegler, et al. ∙ 0 ∙ share

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Unrestricted Adversarial Examples

We introduce a two-player contest for evaluating the safety and robustne...
09/22/2018 ∙ by Tom B. Brown, et al. ∙ 14 ∙ share

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Is Generator Conditioning Causally Related to GAN Performance?

Recent work (Pennington et al, 2017) suggests that controlling the entir...
02/23/2018 ∙ by Augustus Odena, et al. ∙ 0 ∙ share

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Adversarial Patch

We present a method to create universal, robust, targeted adversarial im...
12/27/2017 ∙ by Tom B. Brown, et al. ∙ 0 ∙ share

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Deep reinforcement learning from human preferences

For sophisticated reinforcement learning (RL) systems to interact useful...
06/12/2017 ∙ by Paul Christiano, et al. ∙ 0 ∙ share

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Tom B. Brown

Featured Co-authors

Ian Goodfellow

Ilya Sutskever

Nicholas Carlini

Shane Legg

Colin Raffel

Jan Leike

Augustus Odena

John Schulman

Arvind Neelakantan

Justin Gilmer

Dario Amodei

Scaling Laws for Autoregressive Generative Modeling

Language Models are Few-Shot Learners

Measuring the Algorithmic Efficiency of Neural Networks

Scaling Laws for Neural Language Models

Fine-Tuning Language Models from Human Preferences

Unrestricted Adversarial Examples

Is Generator Conditioning Causally Related to GAN Performance?

Adversarial Patch

Deep reinforcement learning from human preferences