CL High Impact Paper Award
The Computational Linguistics High Impact Paper Award (short form: CL High Impact Paper Award) recognizes papers published in the Computational Linguistics journal within the past 3–5 years that have already demonstrated exceptional scholarly impact. The award was introduced in 2026, and is presented annually at the ACL conference.
As the flagship journal of the ACL community, with over 50 years of scholarly tradition, Computational Linguistics not only publishes high-quality research but also highlights work that shapes subsequent scholarship and advances the discipline as a whole.
About the Award
- Eligibility: Papers published in Computational Linguistics within the past 3–5 years.
- Recognition: At most one paper is selected each year.
- Presentation: The award is announced and presented at the ACL conference, and the authors receive a certificate.
Selection Process
- Papers are first nominated by members of the Computational Linguistics editorial board.
- The committee chairs (the Editor-in-Chief and the Squibs Editor) shortlist the eligible papers each year.
- A committee composed primarily of Computational Linguistics action editors reviews the shortlisted candidates and votes.
Selection Criteria
Selection criteria include scholarly impact, breadth of influence, and depth of contribution.
Award Recipients
| Year | Paper | Authors | Publication |
|---|---|---|---|
| 2026 | Universal Dependencies | Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, Daniel Zeman | Computational Linguistics, Volume 47, Issue 2 (2021) |
2026 Award
The inaugural CL High Impact Paper Award was presented at the ACL 2026 conference to:
- Universal Dependencies, by Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, and Daniel Zeman. Computational Linguistics, 47(2), 2021.
Citation: Universal Dependencies established a unified and cross-linguistically consistent framework for grammatical annotation, fundamentally shaping multilingual NLP research. By enabling scalable syntactic analysis across diverse languages, it catalyzed advances in cross-lingual transfer, multilingual modeling, and grammar-aware methods. Its widespread adoption as a foundational resource for multilingual research and evaluation reflects its exceptional scholarly impact and lasting influence on computational linguistics and natural language processing.
Committee Chairs: Wei Lu (Editor-in-Chief, Computational Linguistics), Michael White (Squibs Editor, Computational Linguistics)