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Designing and Evaluating Language Mo...
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Lee, Mina.
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Designing and Evaluating Language Models for Human Interaction.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Designing and Evaluating Language Models for Human Interaction./
作者:
Lee, Mina.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:
135 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Contained By:
Dissertations Abstracts International85-04B.
標題:
Writing. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30615211
ISBN:
9798380482509
Designing and Evaluating Language Models for Human Interaction.
Lee, Mina.
Designing and Evaluating Language Models for Human Interaction.
- Ann Arbor : ProQuest Dissertations & Theses, 2023 - 135 p.
Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Thesis (Ph.D.)--Stanford University, 2023.
Despite the ubiquity of language models (LMs) in real-world applications (e.g., web search, text autocomplete, and content generation), most LMs are not optimized for, nor are they evaluated on, real-world usage where human users interact with LMs. To address this gap, this dissertation focuses on designing and evaluating LMs for human interaction. We first start by focusing on one specific need that writers encounter in the revision process: coming up with content given surrounding context. To support this need, we propose a training method to enable any pre-trained LMs to accomplish the task of filling in the blanks, helping to better facilitate human-LM interaction. Second, we build a platform, CoAuthor, to capture human-LM interaction as interaction traces. With CoAuthor, we demonstrate how collecting a large interaction dataset and analyzing the traces provide unique insights into LM capabilities regarding language, ideation, and collaboration in human-LM interaction. Lastly, we propose a new evaluation framework, Human-AI Language-based Interaction Evaluation (HALIE), that defines the components of interactive systems and metrics for human-LM interaction tasks beyond writing. Finally, we discuss open challenges and future directions in this field.
ISBN: 9798380482509Subjects--Topical Terms:
551664
Writing.
Designing and Evaluating Language Models for Human Interaction.
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Despite the ubiquity of language models (LMs) in real-world applications (e.g., web search, text autocomplete, and content generation), most LMs are not optimized for, nor are they evaluated on, real-world usage where human users interact with LMs. To address this gap, this dissertation focuses on designing and evaluating LMs for human interaction. We first start by focusing on one specific need that writers encounter in the revision process: coming up with content given surrounding context. To support this need, we propose a training method to enable any pre-trained LMs to accomplish the task of filling in the blanks, helping to better facilitate human-LM interaction. Second, we build a platform, CoAuthor, to capture human-LM interaction as interaction traces. With CoAuthor, we demonstrate how collecting a large interaction dataset and analyzing the traces provide unique insights into LM capabilities regarding language, ideation, and collaboration in human-LM interaction. Lastly, we propose a new evaluation framework, Human-AI Language-based Interaction Evaluation (HALIE), that defines the components of interactive systems and metrics for human-LM interaction tasks beyond writing. Finally, we discuss open challenges and future directions in this field.
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