Tom B. Brown | DeepAI

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∙ 10/28/2020

Scaling Laws for Autoregressive Generative Modeling

We identify empirical scaling laws for the cross-entropy loss in four do...

2 Tom Henighan, et al. ∙

∙ 05/28/2020

Language Models are Few-Shot Learners

Recent work has demonstrated substantial gains on many NLP tasks and ben...

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∙ 05/08/2020

Measuring the Algorithmic Efficiency of Neural Networks

Three factors drive the advance of AI: algorithmic innovation, data, and...

0 Danny Hernandez, et al. ∙

∙ 01/23/2020

Scaling Laws for Neural Language Models

We study empirical scaling laws for language model performance on the cr...

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∙ 09/18/2019

Fine-Tuning Language Models from Human Preferences

Reward learning enables the application of reinforcement learning (RL) t...

0 Daniel M. Ziegler, et al. ∙

∙ 09/22/2018

Unrestricted Adversarial Examples

We introduce a two-player contest for evaluating the safety and robustne...

14 Tom B. Brown, et al. ∙

∙ 02/23/2018

Is Generator Conditioning Causally Related to GAN Performance?

Recent work (Pennington et al, 2017) suggests that controlling the entir...

0 Augustus Odena, et al. ∙

∙ 12/27/2017

Adversarial Patch

We present a method to create universal, robust, targeted adversarial im...

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∙ 06/12/2017

Deep reinforcement learning from human preferences

For sophisticated reinforcement learning (RL) systems to interact useful...

0 Paul Christiano, et al. ∙

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