ACL Test-of-Time Papers Award Recipients

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2021

  • The 2021 winners of the 1996 Test-of-Time Paper Award are:
    • Adam Berger, Stephen Della Pietra, Vicent Della Pietra. A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics, Volume 22, Number 1, March 1996.
    • Jean Carletta. Assessing Agreement on Classification Tasks: The Kappa Statistic. Computational Linguistics, Volume 22, Number 2, June 1996.
  • The 2021 winners of the 2011 Test-of-Time Paper Award are:
    • Maite Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred Stede. Lexicon-Based Methods for Sentiment Analysis. Computational Linguistics, Volume 37, Issue 2, June 2011.
    • Myle Ott, Yejin Choi, Claire Cardie, Jeff Hancock. Finding Deceptive Opinion Spam by Any Stretch of the Imagination. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies.

2020

  • The 2020 winners of the 1995 Test-of-Time Award are:
    • Barbara J. Grosz, Aravind K. Joshi, Scott Weinstein. Centering: A Framework for Modeling the Local Coherence of Discourse. Computational Linguistics, 21(2), June
    • David Yarowsky. Unsupervised Word Sense Disambiguation Rivaling Supervised Methods. 33rd Annual Meeting of the Association for Computational Linguistics
  • The 2020 winners of the 2010 Test-of-Time Award are:
    • Marco Baroni, Alessandro Lenci. Distributional Memory: A General Framework for Corpus-Based Semantics. Computational Linguistics, 36(4), December
    • Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio. Word Representations: A Simple and General Method for Semi-Supervised Learning. 48th Annual Meeting of the Association for Computational Linguistics

2019

  • The 2019 winner of the 1994 Test-of-Time Award is:
    • Bernard Merialdo. Tagging English Text with a Probabilistic Model. Computational Linguistics 20(2), pp. 155–171
  • The 2019 winner of the 2009 Test-of-Time Award is:
    • Theresa Wilson, Janyce Wiebe, Paul Hoffmann. Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment Analysis. Computational Linguistics 35(3), pp. 399–433