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21
A Non-Linear Structural Probe
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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22
Disambiguatory Signals are Stronger in Word-initial Positions
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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23
How (Non-)Optimal is the Lexicon?
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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24
A Bayesian Framework for Information-Theoretic Probing
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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25
How (Non-)Optimal is the Lexicon? ...
NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021
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26
A Non-Linear Structural Probe ...
Abstract: Probes are models devised to investigate the encoding of knowledge—e.g. syntactic structure—in contextual representations. Probes are often designed for simplicity, which has led to restrictions on probe design that may not allow for the full exploitation of the structure of encoded information; one such restriction is linearity. We examine the case of a structural probe (Hewitt and Manning, 2019), which aims to investigate the encoding of syntactic structure in contextual representations through learning only linear transformations. By observing that the structural probe learns a metric, we are able to kernelize it and develop a novel non-linear variant with an identical number of parameters. We test on 6 languages and find that the radial-basis function (RBF) kernel, in conjunction with regularization, achieves a statistically significant improvement over the baseline in all languages—implying that at least part of the syntactic knowledge is encoded non-linearly. We conclude by discussing how the RBF ... : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ...
URL: https://dx.doi.org/10.3929/ethz-b-000518983
http://hdl.handle.net/20.500.11850/518983
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27
How (Non-)Optimal is the Lexicon? ...
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28
Disambiguatory Signals are Stronger in Word-initial Positions ...
Pimentel, Tiago; Cotterell, Ryan; Roark, Brian. - : ETH Zurich, 2021
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29
Finding Concept-specific Biases in Form--Meaning Associations ...
NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021
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30
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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31
Information-Theoretic Probing for Linguistic Structure ...
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32
Information-Theoretic Probing for Linguistic Structure ...
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33
A Corpus for Large-Scale Phonetic Typology ...
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34
Phonotactic Complexity and its Trade-offs ...
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35
Phonotactic Complexity and Its Trade-offs ...
Pimentel, Tiago; Roark, Brian; Cotterell, Ryan. - : ETH Zurich, 2020
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36
A Corpus for Large-Scale Phonetic Typology ...
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37
Predicting Declension Class from Form and Meaning ...
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38
A corpus for large-scale phonetic typology
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39
Predicting declension class from form and meaning
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40
Pareto Probing: Trading Off Accuracy for Complexity
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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