Conflicts of Interest in Published NLP Research 2000-2024
Not on the map. Why?
Abstract (arXiv)
Natural Language Processing research is increasingly reliant on large scale data and computational power. Many achievements in the past decade resulted from collaborations with the tech industry. But an increasing entanglement of academic research and industry interests leads to conflicts of interest. We assessed published NLP research from 2000-2024 and labeled author affiliations as academic or industry-affiliated to measure conflicts of interest. Overall 27.65% of the papers contained at least one industry-affiliated author. That figure increased substantially with more than 1 in 3 papers having a conflict of interest in 2024. We identify top-tier venues (ACL, EMNLP) as main drivers for that effect. The paper closes with a discussion and a simple, concrete suggestion for the future.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 26 references that are in the map. First posted on arXiv 22 Feb 2025.
Builds on
3 of 26 references.
References · 3
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2019The Rise of Multiple Institutional Affiliations in Academiacited by 4
Built on by
Citing papers per year: 2026: 1.
1 paper.