Denis Paperno

In my research, I have been studying meaning in natural language using precise methods, both formal and computational. I am interested in questions like the following:

    • How can we represent meaning?

    • What makes a good meaning representation?

    • What are good ways of learning meaning representations?

    • How do meanings of words interact to derive, for example, the meanings of phrases and sentences?

    • How can one integrate different sources of information - such as images, knowledge bases, and linguistic sources - in a single computational model?

Specific research topic include:

    • neural and distributional approaches to semantics

    • (lexical) semantic typology

    • integrating formal and computational models of semantics

    • quantification

News

    • On December 15, I give a talk at the University of Helsinki.

    • On July 7, I gave a talk at the TALEP seminar at Aix-Marseille University.

Publications: 2022

Publications: 2021

Publications: 2020

Publications: 2019

Publications: 2018

Publications: 2017

    • Denis Paperno and Edward Keenan. Handbook of Quantifiers in Natural Language: Volume 2. Studies in Linguistics and Philosophy 97. Springer, 2017.

    • (in Russian) Denis Paperno and Anna Maloletniaia. Ben iazyk [The Beng language]. Languages of the World: Mande Languages. Edited by Valentin F. Vydrin, Yulia V. Mazurova, Andrej A. Kibrik, Elena B. Markus. St. Petersburg: Nestor-Historia, 2017. Pp. 1000-1031.

    • (In French) Claire Gardent and Denis Paperno. Linguistique informatique et linguistique de terrain [Computational linguistics and field linguistics]. La lettre de l'INSHS. Juillet 2017. Pp. 28-31.

Publications: 2016

    • D. Paperno and M. Baroni. When the whole is less than the sum of its parts. Computational Linguistics 42(2): 345-350.

    • G. Kruszewski, D. Paperno, R. Bernardi and M. Baroni. There is no logical negation here, but there are alternatives. Computational Linguistics 42(4) (special issue on Formal Distributional Semantics): 637-660. The data set described in this article.

    • Alicia Krebs and Denis Paperno. 2016. When Hyperparameters Help: Beneficial Parameter Combinations in Distributional Semantic Models. Proceedings of *SEM 2016 (Fourth Joint Conference on Lexical and Computational Semantics), East Stroudsburg PA: ACL.

    • D. Ryzhova, M. Kyuseva, and D. Paperno. 2016. Typology of adjectives benchmark for compositional distributional models. Proceedings of the 10th Language Resources and Evaluation Conference, 2016: 1253-1257.

    • D. Paperno, G. Kruszewski, A. Lazaridou, Q. Pham, R. Bernardi, S. Pezzelle, M. Baroni, G. Boleda and R. Fernandez. 2016. The LAMBADA dataset: Word prediction requiring a broad discourse context. Proceedings of ACL 2016 (54th Annual Meeting of the Association for Computational Linguistics), East Stroudsburg PA: ACL. Download the dataset!

    • Panchenko A., Ustalov D., Arefyev N., Paperno D. Konstantinova N., Loukachevitch N. and Biemann C. Human and Machine Judgements about Russian Semantic Relatedness. In Proceedings of the 5th Conference on Analysis of Images, Social Networks and Texts (AIST'2016). Communications in Computer and Information Science (CCIS). Springler-Verlag Berlin Heidelberg

    • Alicia Krebs and Denis Paperno. 2016. Capturing Discriminative Attributes in a Distributional Space: Task Proposal. Presented at RepEval 2016: The First Workshop on Evaluating Vector Space Representations for NLP. Berlin, Germany.

Publications: 2015

Publications: 2014

Major earlier work (see this page for more papers)

Research interests

I am assistant professor of Computational Linguistics at Utrecht University, currently in détachement from my researcher position at CNRS (the National Center of Scientific Research). After receiving a PhD in Linguistics from the University of California Los Angeles, I worked at the University of Trento in Marco Baroni's group.

Check out Curriculum Vitae for more information.