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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ... Maudslay, Rowan Hall; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 2 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth. - : arXiv, 2020 BASE Show details 3 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan Hall; Zmigrod, Ran; Williams, Adina; Cotterell, Ryan. - : arXiv, 2020 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 BASE Hide details 4 Metaphor Detection Using Context and Concreteness Maudslay, Rowan Hall; Pimentel, Tiago; Cotterell, Ryan... In: Proceedings of the Second Workshop on Figurative Language Processing (2020) BASE Show details 5 A Tale of a Probe and a Parser ... Maudslay, Rowan Hall; Valvoda, Josef; Pimentel, Tiago. - : arXiv, 2020 BASE Show details

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