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1
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
In: https://hal.inria.fr/hal-03161685 ; 2021 (2021)
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2
Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi
In: https://hal.inria.fr/hal-03161677 ; 2021 (2021)
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3
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
In: EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03239087 ; EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kyiv / Virtual, Ukraine ; https://2021.eacl.org/ (2021)
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4
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
In: NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.inria.fr/hal-03251105 ; NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2021, Mexico City, Mexico (2021)
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5
Building a User-Generated Content North-African Arabizi Treebank: Tackling Hell
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02889804 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, Canada. ⟨10.18653/v1/2020.acl-main.107⟩ (2020)
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6
CamemBERT: a Tasty French Language Model
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02889805 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. ⟨10.18653/v1/2020.acl-main.645⟩ (2020)
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7
Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03161637 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. pp.538-555, ⟨10.18653/v1/2020.acl-main.51⟩ (2020)
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8
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
In: https://hal.inria.fr/hal-03109106 ; 2020 (2020)
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9
CamemBERT: a Tasty French Language Model
In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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10
What does BERT learn about the structure of language?
In: ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02131630 ; ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Jul 2019, Florence, Italy (2019)
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11
Contextualized Diachronic Word Representations
In: 1st International Workshop on Computational Approaches to Historical Language Change 2019 (colocated with ACL 2019) ; https://hal.archives-ouvertes.fr/hal-02194763 ; 1st International Workshop on Computational Approaches to Historical Language Change 2019 (colocated with ACL 2019), Aug 2019, Florence, Italy (2019)
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12
Cheating a Parser to Death: Data-driven Cross-Treebank Annotation Transfer
In: Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; https://hal.inria.fr/hal-01798801 ; Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Miyazaki, Japan (2018)
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13
CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing
In: 11th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-01786125 ; 11th Language Resources and Evaluation Conference, May 2018, Miyazaki, Japan ; http://lrec2018.lrec-conf.org (2018)
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14
The ParisNLP entry at the ConLL UD Shared Task 2017: A Tale of a #ParsingTragedy
In: Conference on Computational Natural Language Learning ; https://hal.inria.fr/hal-01584168 ; Conference on Computational Natural Language Learning, Aug 2017, Vancouver, Canada. pp.243-252, ⟨10.18653/v1/K17-3026⟩ ; http://universaldependencies.org/conll17/ (2017)
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15
Paris and Stanford at EPE 2017: Downstream Evaluation of Graph-based Dependency Representations
In: EPE 2017 - The First Shared Task on Extrinsic Parser Evaluation ; https://hal.inria.fr/hal-01592051 ; EPE 2017 - The First Shared Task on Extrinsic Parser Evaluation, Sep 2017, Pisa, Italy. pp.47-59 ; http://epe.nlpl.eu (2017)
Abstract: International audience ; We describe the STANFORD-PARIS and PARIS-STANFORD submissions to the 2017 Extrinsic Parser Evaluation (EPE) Shared Task. The purpose of this shared task was to evaluate dependency graphs on three downstream tasks. Through our submissions, we evaluated the usability of several representations derived from English Universal Dependencies (UD), as well as the Stanford Dependencies (SD), Predicate Argument Structure (PAS), and DM representations. We further compared two parsing strategies: Directly parsing to graph-based dependency representations and a two-stage process of first parsing to surface syntax trees and then applying rule-based augmentations to obtain the final graphs. Overall, our systems performed very well and our submissions ranked first and third. In our analysis, we find that the two-stage parsing process leads to better downstream performance, and that enhanced UD, a graph-based representation, consistently outperforms basic UD, a strict surface syntax representation, suggesting an advantage of enriched representations for downstream tasks.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
URL: https://hal.inria.fr/hal-01592051/file/epe17.pdf
https://hal.inria.fr/hal-01592051/document
https://hal.inria.fr/hal-01592051
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16
Building a Question Treebank for French : The French QuestionBank ; Tour d'Horizon du French QuestionBank : Construire un Corpus Arboré de Questions pour le Français
In: ACor4French - Les corpus annotés du français ; https://hal.inria.fr/hal-01682869 ; ACor4French - Les corpus annotés du français, Jun 2017, Orléans, France (2017)
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17
From Noisy Questions to Minecraft Texts: Annotation Challenges in Extreme Syntax Scenarios
In: 2nd Workshop on Noisy User-generated Text (W-NUT) at CoLing 2016 ; https://hal.inria.fr/hal-01584054 ; 2nd Workshop on Noisy User-generated Text (W-NUT) at CoLing 2016, Dec 2016, Osaka, Japan (2016)
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18
Hard Time Parsing Questions: Building a QuestionBank for French
In: Tenth International Conference on Language Resources and Evaluation (LREC 2016) ; https://hal.archives-ouvertes.fr/hal-01457184 ; Tenth International Conference on Language Resources and Evaluation (LREC 2016), May 2016, Portorož, Slovenia (2016)
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