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21
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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22
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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23
Parameter space factorization for zero-shot learning across tasks and languages ...
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24
Analogy Training Multilingual Encoders ...
Garneau, Nicolas; Hartmann, Mareike; Sandholm, Anders. - : Apollo - University of Cambridge Repository, 2021
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25
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : Apollo - University of Cambridge Repository, 2021
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26
UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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27
How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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28
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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29
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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30
Multilingual and Cross-Lingual Intent Detection from Spoken Data ...
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31
Semantic Data Set Construction from Human Clustering and Spatial Arrangement ...
Majewska, Olga; McCarthy, Diana; Van Den Bosch, Jasper JF. - : Apollo - University of Cambridge Repository, 2021
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32
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
Abstract: Capturing word meaning in context and distinguishing between correspondences and variations across languages is key to building successful multilingual and cross-lingual text representation models. However, existing multilingual evaluation datasets that evaluate lexical semantics "in-context" have various limitations. In particular, 1) their language coverage is restricted to high-resource languages and skewed in favor of only a few language families and areas, 2) a design that makes the task solvable via superficial cues, which results in artificially inflated (and sometimes super-human) performances of pretrained encoders, on many target languages, which limits their usefulness for model probing and diagnostics, and 3) little support for cross-lingual evaluation. In order to address these gaps, we present AM2iCo (Adversarial and Multilingual Meaning in Context), a wide-coverage cross-lingual and multilingual evaluation set; it aims to faithfully assess the ability of state-of-the-art (SotA) representation ... : EMNLP 2021 long paper ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2104.08639
https://dx.doi.org/10.48550/arxiv.2104.08639
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33
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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34
Parameter space factorization for zero-shot learning across tasks and languages
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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35
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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36
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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37
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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38
Verb Knowledge Injection for Multilingual Event Processing ...
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39
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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40
Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021
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