Collaboration or Corporate Capture? Quantifying NLP's Reliance on Industry Artifacts and Contributions
This work highlights a potential issue of corporate influence in NLP research, raising questions about collaboration and independence in the field.
The study surveyed 100 papers from EMNLP 2022 to quantify NLP researchers' reliance on industry-produced models and artifacts, finding that citation of these resources is at least three times higher than expected.
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) benchmarks and correspondingly to stay relevant in NLP research. We surveyed 100 papers published at EMNLP 2022 to determine the degree to which 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. Our work serves as a scaffold to enable future researchers to more accurately address whether: 1) Collaboration with industry is still collaboration in the absence of an alternative or 2) if NLP inquiry has been captured by the motivations and research direction of private corporations.