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
Denis Paperno. On learning an interpreted language with recurrent models. Computational Linguistics. Computational Linguistics 48 (2): 471–482.
Timothee Mickus, Denis Paperno, and Mathieu Constant. How to Dissect a Muppet: The Structure of Transformer Embedding Spaces. Transactions of the Association for Computational Linguistics (2022) 10: 981–996.
Timothee Mickus, Kees van Deemter, Mathieu Constant, and Denis Paperno. Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings.
Ryzhova, D. and Paperno, D., 2022. Constructing a typological questionnaire with distributional semantic models. In E. Rakhilina and T. Reznikova (eds.), The Typology of Physical Qualities. John Benjamins, pp. 309-328.
Publications: 2021
Timothee Mickus, Mathieu Constant, and Denis Paperno. A Game Interface to Study Semantic Grounding in Text-Based Models. In Proceedings of the 3rd IEEE Conference on Games.
Timothee Mickus, Mathieu Constant, and Denis Paperno. About Neural Networks and Writing Definitions. Dictionaries: Journal of the Dictionary Society of North America, Volume 42, Issue 2, 2021, pp. 95-117
Publications: 2020
Mickus, T., Bernard, T. and Paperno, D., 2020, December. What Meaning-Form Correlation Has to Compose With: A Study of MFC on Artificial and Natural Language. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 3737-3749).
Timothee Mickus, Denis Paperno, Mathieu Constant, and Kees van Deemter. What do you mean, BERT? Assessing BERT as a Distributional Semantics Model. Proceedings of the Society for Computation in Linguistics: Vol. 3 , Article 34.
Nikiforova, S., Deoskar, T., Paperno, D. and Winter, Y., 2020, December. Geo-Aware Image Caption Generation. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 3143-3156).
(in French) Mickus, T., Constant, M. and Paperno, D., 2020. Génération automatique de définitions pour le français (Definition Modeling in French). In Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2: Traitement Automatique des Langues Naturelles (pp. 66-80).
Publications: 2019
Timothee Mickus, Denis Paperno, Mathieu Constant. Mark my Word: A Sequence-to-Sequence Approach to Definition Modeling. Proceedings of The First NLPL Workshop on Deep Learning for Natural Language Processing, Turku, pp. 1-11.
Lin Li, Kees van Deemter, Denis Paperno, Jingyu Fan. Choosing between Long and Short Word Forms in Mandarin. Proceedings of the 12th International Conference on Natural Language Generation, pp. 34–39.
Denis Paperno and Daria Ryzhova. Automatic construction of lexical typological questionnaires. In Language Documentation and Conservation: Special issue on Methodological Tools for Linguistic Description and Typology, ed. by Aimée Lahaussois and Marine Vuillermet, pp. 45-61. Associated data: 100 questionnaires described in the paper.
Mickus, Timothee; Bonami, Olivier; and Paperno, Denis (2019). Distributional Effects of Gender Contrasts Across Categories, Proceedings of the Society for Computation in Linguistics: Vol. 2 , Article 19
Publications: 2018
Denis Paperno. Limitations in learning an interpreted language with recurrent models. More complete preprint version. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pp. 384–386.
Anupama Chingacham and Denis Paperno. Generalizing Representations of Lexical Semantic Relations. Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018), Torino, Italy, December 10-12, 2018.
Olivier Bonami and Denis Paperno. A characterisation of the inflection-derivation opposition in a distributional vector space. Preprint version. Lingue e Linguaggio VII.2 (2018), pp. 173-196.
Alicia Krebs, Alessandro Lenci and Denis Paperno. SemEval-2018 Task 10: Capturing Discriminative Attributes. Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Pp. 732–740.
Ryzhova D.A., Меlnik A.A., Yershov I.A., Panteleeva I. M., Paperno D.A., Singh Ya., Sobolev M. Automatic data collection in lexical typology. Proceedings of Computational Linguistics and Intellectual Technologies (Dialog) conference 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
G. Kruszewski, D. Paperno and M. Baroni. 2015. Deriving Boolean structures from distributional vectors. Transactions of the Association for Computational Linguistics 3: 375-388.
Panchenko A., Loukachevitch N. V., Ustalov D., Paperno D., Meyer C. M., Konstantinova N. RUSSE: The First International Workshop on Russian Semantic Similarity. In Proceedings of International Conference on Computational Linguistics Dialogue 2015
S. Ritter, C. Long, D. Paperno, M. Baroni, M. Botvinick and A. Goldberg. 2015. Leveraging preposition ambiguity to assess compositional distributional models of semantics. Proceedings of *SEM 2015 (Fourth Joint Conference on Lexical and Computational Semantics), East Stroudsburg PA: ACL, 199-204.
R. Bernardi, G. Boleda, R. Fernandez and D. Paperno. 2015. Distributional semantics in use. Proceedings of LSD 2015 (First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics), East Stroudsburg PA: ACL, 95-101.
Publications: 2014
D. Paperno, N. Pham and M. Baroni. 2014. A practical and linguistically-motivated approach to compositional distributional semantics. Proceedings of ACL 2014 (52nd Annual Meeting of the Association for Computational Linguistics), East Stroudsburg PA: ACL, 90-99. Code for the PLF model.
D. Paperno, M. Marelli, K. Tentori and M. Baroni. 2014. Corpus-based estimates of word association predict biases in judgment of word co-occurrence likelihood. Cognitive Psychology 74: 66-83.
Grammatical description of Beng, a Mande language spoken in Cote d'Ivoire. Appeared in Mandenkan 51, 2014.
An Alternative semantics for Negative Conjunction in Russian. To appear. Proceedings of FASL 23, Michigan Slavic Publications, 2014.
M.Hurlimann, R. Bernardi and D. Paperno. Nominal Coercion in Space. Proceedings of CLIC-it 2014.
Major earlier work (see this page for more papers)
PhD Thesis: Semantics and Syntax of Non-Standard Coordination. UCLA, 2012.
Conjunction is parallel computation. Proceedings of SALT 22: 403–423, 2012.
The Handbook of Quantifiers in Natural Language (co-edited with Ed Keenan) explores typological variation of quantifier structures across languages. The first volume appeared in 2012, the second one in 2017.
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.