Search Results for author: Abraham J. Fetterman

Found 5 papers, 2 papers with code

On the Stepwise Nature of Self-Supervised Learning

1 code implementation27 Mar 2023 James B. Simon, Maksis Knutins, Liu Ziyin, Daniel Geisz, Abraham J. Fetterman, Joshua Albrecht

We present a simple picture of the training process of joint embedding self-supervised learning methods.

Self-Supervised Learning

Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety

no code implementations13 Dec 2022 Joshua Albrecht, Ellie Kitanidis, Abraham J. Fetterman

Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and text summarization.

Common Sense Reasoning Ethics +2

Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds

1 code implementation24 Oct 2022 Joshua Albrecht, Abraham J. Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski, Nicole Seo, Michael Rosenthal, Maksis Knutins, Zachary Polizzi, James B. Simon, Kanjun Qiu

As a benchmark tailored for studying RL generalization, we introduce Avalon, a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards.

Navigate Reinforcement Learning (RL)

SoftAdam: Unifying SGD and Adam for better stochastic gradient descent

no code implementations25 Sep 2019 Abraham J. Fetterman, Christina H. Kim, Joshua Albrecht

Abstract Stochastic gradient descent (SGD) and Adam are commonly used to optimize deep neural networks, but choosing one usually means making tradeoffs between speed, accuracy and stability.

Image Classification Language Modelling

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