Scholarly Migration Patterns in Natural Language Processing

A study analyzing NLP research from 2010 to 2026 finds that the disciplinary center of gravity is shifting as Large Language Model advances blur lines between NLP and general Machine Learning.

• Established authors lost 19.2 percentage points of share at flagship ACL main-conference tracks while gaining 14.8 percentage points in newer Findings tracks, with general ML venues rising 8.6 percentage points.
• Among newer authors debuting with at least three first-author NLP-topic papers, the share publishing mostly at ACL venues fell from 84% in 2019 to 74% in 2024.
• The share of new authors publishing mostly at general ML venues rose from 5% to 21%, with causal inference indicating these venues confer a significant citation premium that influences selection.