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A Latent-Variable Model for Intrinsic Probing ...
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On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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Intrinsic Probing through Dimension Selection ...
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Information-Theoretic Probing for Linguistic Structure ...
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Information-Theoretic Probing for Linguistic Structure ...
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Intrinsic Probing through Dimension Selection ...
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11
Predicting Declension Class from Form and Meaning ...
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Predicting declension class from form and meaning
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Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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14
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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15
Predicting Declension Class from Form and Meaning
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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16
A Tale of a Probe and a Parser
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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17
Intrinsic Probing through Dimension Selection
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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18
Information-Theoretic Probing for Linguistic Structure
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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19
Pareto Probing: Trading Off Accuracy for Complexity ...
Abstract: The question of how to probe contextual word representations for linguistic structure in a way that is both principled and useful has seen significant attention recently in the NLP literature. In our contribution to this discussion, we argue for a probe metric that reflects the fundamental trade-off between probe complexity and performance: the Pareto hypervolume. To measure complexity, we present a number of parametric and non-parametric metrics. Our experiments using Pareto hypervolume as an evaluation metric show that probes often do not conform to our expectations---e.g., why should the non-contextual fastText representations encode more morpho-syntactic information than the contextual BERT representations? These results suggest that common, simplistic probing tasks, such as part-of-speech labeling and dependency arc labeling, are inadequate to evaluate the linguistic structure encoded in contextual word representations. This leads us to propose full dependency parsing as a probing task. In support of ... : Tiago Pimentel and Naomi Saphra contributed equally to this work. Camera ready version of EMNLP 2020 publication. Code available in https://github.com/rycolab/pareto-probing ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://arxiv.org/abs/2010.02180
https://dx.doi.org/10.48550/arxiv.2010.02180
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A Tale of a Probe and a Parser ...
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