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This study analyzes the shifting publication patterns in Natural Language Processing (NLP) as it intersects with Machine Learning (ML), revealing a notable migration of authors from traditional NLP venues to general ML conferences. By comparing publication data from 2010 to 2026, the authors found that established researchers have decreased their presence in flagship ACL tracks while increasing their contributions to newer findings tracks and general ML venues. Furthermore, newer authors are increasingly favoring general ML venues, which are associated with a significant citation premium, indicating a fundamental change in the disciplinary landscape of NLP research.
Established NLP researchers are migrating to general ML venues, with citation benefits influencing their publication choices.
Natural Language Processing (NLP) has traditionally been published in its core disciplinary venues like ACL. However, advances in Large Language Models (LLMs) has led to a blurring of the disciplinary lines between NLP and general Machine Learning (ML), with authors regularly publishing in venues from both fields. Here, we ask whether the disciplinary center of gravity is shifting. Using NLP research published from 2010 to 2026 and studies of both established and new authors, we find that a migration is taking place. First, comparing the pre- and post-LLM eras, established authors lost 19.2pp of share at flagship *ACL main-conference tracks while gaining 14.8pp in the newer Findings tracks, and general ML venues rose 8.6pp, even when adjusting for parallel growth in the fields. Second, among newer authors who debut with at least three first-author NLP-topic papers, the share whose work appears mostly at *ACL venues fell from 84% (2019) to 74% (2024), while the share appearing mostly at general ML venues rose from 5% to 21%. Using causal inference techniques, we estimate that these general ML venues confer a significant citation premium, which influences venue selection. Together, these results point to a significant shift in where NLP research is published.
