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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 ...
Abstract: The success of neural networks on a diverse set of NLP tasks has led researchers to question how much these networks actually ``know'' about natural language. Probes are a natural way of assessing this. When probing, a researcher chooses a linguistic task and trains a supervised model to predict annotations in that linguistic task from the network's learned representations. If the probe does well, the researcher may conclude that the representations encode knowledge related to the task. A commonly held belief is that using simpler models as probes is better; the logic is that simpler models will identify linguistic structure, but not learn the task itself. We propose an information-theoretic operationalization of probing as estimating mutual information that contradicts this received wisdom: one should always select the highest performing probe one can, even if it is more complex, since it will result in a tighter estimate, and thus reveal more of the linguistic information inherent in the representation. ... : Accepted for publication at ACL 2020. This is the camera ready version. Code available in https://github.com/rycolab/info-theoretic-probing ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.2004.03061
https://arxiv.org/abs/2004.03061
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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 ...
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20
A Tale of a Probe and a Parser ...
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