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Operationalizing Language for Machin...

Mu, Jesse L.

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Operationalizing Language for Machine Learning: Supervision, Interpretation, and Communication.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Operationalizing Language for Machine Learning: Supervision, Interpretation, and Communication./
Author:	Mu, Jesse L.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	149 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Contained By:	Dissertations Abstracts International85-04B.
Subject:	Communication. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30615213
ISBN:	9798380484978

Operationalizing Language for Machine Learning: Supervision, Interpretation, and Communication.
Mu, Jesse L.

Operationalizing Language for Machine Learning: Supervision, Interpretation, and Communication. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 149 p.

Source: Dissertations Abstracts International, Volume: 85-04, Section: B.

Thesis (Ph.D.)--Stanford University, 2023.

Language is a uniquely powerful tool for conceptualizing the world that allows humans to teach, understand, and collaborate with each other. This dissertation surveys three ways in which language can similarly improve the performance and usability of machine learning systems across a variety of tasks and modalities. First, supervision: we use language abstractions to help regularize models and agents for improved performance, even for downstream tasks in vision and reinforcement learning that do not necessarily require language understanding. Second, interpretation: we use language and compositionality to generate explanations of the neurons inside deep neural networks, allowing us to understand and even control model behavior. Finally, communication: we study a class of multiagent signaling games, helping agents learn more robust and interpretable languages by encouraging them to express the generalizations encoded in human languages.

ISBN: 9798380484978Subjects--Topical Terms:

524709
Communication.

Operationalizing Language for Machine Learning: Supervision, Interpretation, and Communication.
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