Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work

Scholars often explore literature outside of their home community of study. This exploration process is frequently hampered by field-specific jargon. Past computational work often focuses on supporting translation work by removing jargon through simplification and summarization; here, we explore a different approach that preserves jargon as useful bridges to new conceptual spaces. Specifically, we cast different scholarly domains as different language-using communities, and explore how to adapt techniques from unsupervised cross-lingual alignment of word embeddings to explore conceptual alignments between domain-specific word embedding spaces.We developed a prototype cross-domain search engine that uses aligned domain-specific embeddings to support conceptual exploration, and tested this prototype in two case studies. We discuss qualitative insights into the promises and pitfalls of this approach to translation work, and suggest design insights for future interfaces that provide computational support for cross-domain information seeking.

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Publication Details

Published
2025-03-19
DOI
https://doi.org/10.1145/3708359.3712110
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
4.96

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article

Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work

Joel Chan, Calvin Bao, Yow-Ting Shiue, Marine Carpuat
2 citations
Natural Language Processing Techniques
4.96
article

Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work

Joel Chan, Calvin Bao, Yow-Ting Shiue, Marine Carpuat
article en
2 citations

Abstract

Scholars often explore literature outside of their home community of study. This exploration process is frequently hampered by field-specific jargon. Past computational work often focuses on supporting translation work by removing jargon through simplification and summarization; here, we explore a different approach that preserves jargon as useful bridges to new conceptual spaces. Specifically, we cast different scholarly domains as different language-using communities, and explore how to adapt techniques from unsupervised cross-lingual alignment of word embeddings to explore conceptual alignments between domain-specific word embedding spaces.We developed a prototype cross-domain search engine that uses aligned domain-specific embeddings to support conceptual exploration, and tested this prototype in two case studies. We discuss qualitative insights into the promises and pitfalls of this approach to translation work, and suggest design insights for future interfaces that provide computational support for cross-domain information seeking.

University of Maryland, College Park (US)
Office of Naval Research
Quality Education
Openalex Percentile: Top 6%
Natural Language Processing Techniques
4.96
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