1 |
Plongements Interprétables pour la Détection de Biais Cachés
|
|
|
|
In: à paraître : Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles (TALN 2021) ; https://hal.archives-ouvertes.fr/hal-03265888 ; Traitement Automatique des Langues Naturelles (TALN 2021), 2021, Lille, France. pp.64-80 ; https://talnrecital2021.inria.fr/articles-acceptes/ (2021)
|
|
BASE
|
|
Show details
|
|
2 |
Prédire l'aspect linguistique en anglais au moyen de transformers
|
|
|
|
In: à paraître : Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles (TALN 2021) ; https://hal.archives-ouvertes.fr/hal-03265894 ; Traitement Automatique des Langues Naturelles (TALN 2021), 2021, Lille, France. pp.209-218 ; https://talnrecital2021.inria.fr/articles-acceptes/ (2021)
|
|
BASE
|
|
Show details
|
|
3 |
Composition of Embeddings : Lessons from Statistical Relational Learning
|
|
|
|
In: Proceedings of SEM 2019 ; 8th Joint Conference on Lexical and Computational Semantics (SEM 2019) ; https://hal.archives-ouvertes.fr/hal-02397476 ; 8th Joint Conference on Lexical and Computational Semantics (SEM 2019), Jun 2019, Minneapolis, United States. pp.33-43 (2019)
|
|
Abstract:
International audience ; Various NLP problems -- such as the prediction of sentence similarity, entailment, and discourse relations -- are all instances of the same general task: the modeling of semantic relations between a pair of textual elements. A popular model for such problems is to embed sentences into fixed size vectors, and use composition functions (e.g. concatenation or sum) of those vectors as features for the prediction. At the same time, composition of embeddings has been a main focus within the field of Statistical Relational Learning (SRL) whose goal is to predict relations between entities (typically from knowledge base triples). In this article, we show that previous work on relation prediction between texts implicitly uses compositions from baseline SRL models. We show that such compositions are not expressive enough for several tasks (e.g. natural language inference). We build on recent SRL models to address textual relational problems, showing that they are more expressive, and can alleviate issues from simpler compositions. The resulting models significantly improve the state of the art in both transferable sentence representation learning and relation prediction.
|
|
Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Embeddings; Relational learning
|
|
URL: https://hal.archives-ouvertes.fr/hal-02397476/file/sileo_24995.pdf https://hal.archives-ouvertes.fr/hal-02397476 https://hal.archives-ouvertes.fr/hal-02397476/document
|
|
BASE
|
|
Hide details
|
|
4 |
Mining Discourse Markers for Unsupervised Sentence Representation Learning
|
|
|
|
In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2019) ; https://hal.archives-ouvertes.fr/hal-02397473 ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2019), Jun 2019, Minneapolis, United States. pp.3477-3486 (2019)
|
|
BASE
|
|
Show details
|
|
5 |
Content vs. function words: The view from distributional semantics ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Content vs. function words: The view from distributional semantics
|
|
|
|
In: Sinn und Bedeutung; Bd. 22 Nr. 1 (2018): Proceedings of Sinn und Bedeutung 22; 1-21 ; Proceedings of Sinn und Bedeutung; Vol 22 No 1 (2018): Proceedings of Sinn und Bedeutung 22; 1-21 ; 2629-6055 (2019)
|
|
BASE
|
|
Show details
|
|
8 |
Lexical vs. logical words: the view from Distributional Semantics
|
|
|
|
In: Proceedings fo Sinn und Bedeutung ; https://halshs.archives-ouvertes.fr/halshs-02381667 ; Proceedings fo Sinn und Bedeutung, 2018, Berlin, Germany (2018)
|
|
BASE
|
|
Show details
|
|
9 |
Content vs. function words: the view from distributional semantics
|
|
|
|
In: ISSN: 1435-9588 ; ZAS Papers in Linguistics (ZASPiL) ; https://jeannicod.ccsd.cnrs.fr/ijn_03247051 ; ZAS Papers in Linguistics (ZASPiL), Leibniz-Zentrum Allgemeine Sprachwissenschaft (ZAS) 2018, Proceedings of Sinn und Bedeutung 22, 1, 60, pp.1-21. ⟨10.21248/zaspil.60.2018.451⟩ ; https://zaspil.leibniz-zas.de/article/view/451 (2018)
|
|
BASE
|
|
Show details
|
|
10 |
Content vs. function words: the view from distributional semantics ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Système d’ensemble pour la classification de tweets, DEFT 2017
|
|
|
|
In: Atelier Défi Fouille de Textes : Analyse d'opinion et langage figuratif dans des tweets en français@ TALN/RECITAL 2017 (DEFT 2017) ; https://hal.archives-ouvertes.fr/hal-03120281 ; Atelier Défi Fouille de Textes : Analyse d'opinion et langage figuratif dans des tweets en français@ TALN/RECITAL 2017 (DEFT 2017), Jun 2017, Orléans, France. pp.27-31 ; http://talnarchives.atala.org/ateliers/2017/DEFT/2.pdf (2017)
|
|
BASE
|
|
Show details
|
|
12 |
Types, meanings and co-composition in lexical semantics
|
|
|
|
In: Modern Perspectives in Type-Theoretical Semantics ; https://hal.archives-ouvertes.fr/hal-03131888 ; Chatzikyriakidis, Stergios; Zhaohui, Luo. Modern Perspectives in Type-Theoretical Semantics, 98, Springer, pp.135--161, 2017, Studies in Linguistics and Philosophy book series (SLAP), 978-3319504209. ⟨10.1007/978-3-319-50422-3_6⟩ ; https://link.springer.com/chapter/10.1007/978-3-319-50422-3_6 (2017)
|
|
BASE
|
|
Show details
|
|
14 |
Integrating Type Theory and Distributional Semantics: A Case Study on Adjective–Noun Compositions
|
|
|
|
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal-ens.archives-ouvertes.fr/hal-01678831 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2016, 42 (4), pp.703 - 725. ⟨10.1162/COLI_a_00264⟩ (2016)
|
|
BASE
|
|
Show details
|
|
16 |
A Generalisation of Lexical Functions for Composition in Distributional Semantics
|
|
|
|
In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) ; 53rd Annual Meeting of the Association for Computational Linguistics (ACL 2015) ; https://hal.archives-ouvertes.fr/hal-02355284 ; 53rd Annual Meeting of the Association for Computational Linguistics (ACL 2015), Jul 2015, Beijing, China. pp.281-291 (2015)
|
|
BASE
|
|
Show details
|
|
17 |
Lexical semantics today
|
|
|
|
In: The Routledge Handbook of Linguistics - 2015 ; https://hal.archives-ouvertes.fr/hal-03213958 ; Allan Keith. The Routledge Handbook of Linguistics - 2015, Routledge, pp.169--201, 2015, 978-0415832571. ⟨10.4324/9781315718453⟩ ; https://www.routledgehandbooks.com/doi/10.4324/9781315718453.ch11 (2015)
|
|
BASE
|
|
Show details
|
|
18 |
Quantitative methods for identifying systematic polysemy classes
|
|
|
|
In: Proceedings of the 6th Conference on Quantitative Investigations in Theoretical Linguistics ; 6th Conference on Quantitative Investigations in Theoretical Linguistics (QITL 2015) ; https://hal.archives-ouvertes.fr/hal-02397478 ; 6th Conference on Quantitative Investigations in Theoretical Linguistics (QITL 2015), Nov 2015, Tübingen, Germany. pp.1-5 (2015)
|
|
BASE
|
|
Show details
|
|
19 |
Quantitative methods for identifying systematic polysemy classes ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Quantitative methods for identifying systematic polysemy classes
|
|
|
|
BASE
|
|
Show details
|
|
|
|