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1
Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP
In: https://hal.inria.fr/hal-03540069 ; 2022 (2022)
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2
Automatic Normalisation of Early Modern French
In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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3
Towards a Cleaner Document-Oriented Multilingual Crawled Corpus
In: https://hal.inria.fr/hal-03536361 ; 2022 (2022)
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4
Rethinking Automatic Evaluation in Sentence Simplification
In: https://hal.inria.fr/hal-03199901 ; 2021 (2021)
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5
Multilingual Unsupervised Sentence Simplification
In: https://hal.inria.fr/hal-03109299 ; 2021 (2021)
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6
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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7
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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8
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
In: https://hal.inria.fr/hal-03177623 ; 2021 (2021)
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9
Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering
In: https://hal.inria.fr/hal-03109187 ; 2021 (2021)
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10
Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios? ...
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11
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT ...
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12
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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13
Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi ...
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14
Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering ...
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15
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models ...
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16
MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases ...
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17
ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations ...
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18
Controllable Sentence Simplification
In: https://hal.inria.fr/hal-02445874 ; 2019 (2019)
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19
CamemBERT: a Tasty French Language Model
In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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20
Modeling German Verb Argument Structures: LSTMs vs. Humans
In: https://hal.archives-ouvertes.fr/hal-02417640 ; 2019 (2019)
Abstract: LSTMs have proven very successful at language modeling. However, it remains unclear to what extent they are able to capture complex morphosyntactic structures. In this paper, we examine whether LSTMs are sensitive to verb argument structures. We introduce a German grammaticality dataset in which ungrammatical sentences are constructed by manipulating case assignments (eg substituting nominative by accusative or dative). We find that LSTMs are better than chance in detecting incorrect argument structures and slightly worse than humans tested on the same dataset. Surprisingly, LSTMs are contaminated by heuristics not found in humans like a preference toward nominative noun phrases. In other respects they show human-similar results like biases for particular orders of case assignments.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
URL: https://hal.archives-ouvertes.fr/hal-02417640/file/1912.00239.pdf
https://hal.archives-ouvertes.fr/hal-02417640/document
https://hal.archives-ouvertes.fr/hal-02417640
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