To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing

October 11, 2023 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Sireesh Gururaja, Amanda Bertsch, Clara Na, David Gray Widder, Emma Strubell arXiv ID 2310.07715 Category cs.CL: Computation & Language Cross-listed cs.CY Citations 6 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 5 months ago
Abstract
NLP is in a period of disruptive change that is impacting our methodologies, funding sources, and public perception. In this work, we seek to understand how to shape our future by better understanding our past. We study factors that shape NLP as a field, including culture, incentives, and infrastructure by conducting long-form interviews with 26 NLP researchers of varying seniority, research area, institution, and social identity. Our interviewees identify cyclical patterns in the field, as well as new shifts without historical parallel, including changes in benchmark culture and software infrastructure. We complement this discussion with quantitative analysis of citation, authorship, and language use in the ACL Anthology over time. We conclude by discussing shared visions, concerns, and hopes for the future of NLP. We hope that this study of our field's past and present can prompt informed discussion of our community's implicit norms and more deliberate action to consciously shape the future.
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