Collaboration or Corporate Capture? Quantifying NLP’s Reliance on Industry Artifacts and Contributions

Anonymous

Abstract: Impressive performance of pre-trained models has garnered public attention and made news headlines in recent years. Almost always, these models are produced by or in collaboration with industry. Using them is critical for competing on natural language processing (NLP) bench-marks and correspondingly to stay relevant in NLP research. We surveyed 100 papers published at EMNLP 2022 to determine to what degree researchers rely on industry models, other artifacts, and contributions to publish in prestigious NLP venues and found that the ratio of their citation is at least three times greater than what would be expected. We discuss two possible perspectives regarding NLP’s increasing reliance on industry: 1) Is collaboration withindustry still collaboration in the absence of an alternative? Or 2) has NLP inquiry been captured by the motivations and research direction of private corporations?

Paper Type: long

Research Area: Ethics, Bias, and Fairness

Contribution Types: Data resources, Data analysis, Surveys

Languages Studied: English