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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 – 10 of 10 1 Training dynamics of neural language models ... Saphra, Naomi. - : The University of Edinburgh, 2021 BASE Show details 2 A Non-Linear Structural Probe Pimentel, Tiago; Cotterell, Ryan; Saphra, Naomi... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 3 A Non-Linear Structural Probe ... White, Jennifer C.; Pimentel, Tiago; Saphra, Naomi. - : ETH Zurich, 2021 BASE Show details 4 Training dynamics of neural language models Saphra, Naomi. - : The University of Edinburgh, 2021 BASE Show details 5 Pareto Probing: Trading Off Accuracy for Complexity Saphra, Naomi; Cotterell, Ryan; Pimentel, Tiago... In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 6 Pareto Probing: Trading Off Accuracy for Complexity ... Pimentel, Tiago; Saphra, Naomi; Williams, Adina; Cotterell, Ryan. - : arXiv, 2020 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 BASE Hide details 7 Understanding Learning Dynamics Of Language Models with SVCCA ... Saphra, Naomi; Lopez, Adam. - : arXiv, 2018 BASE Show details 8 Pynlpl: V0.7.7.1 ... Gompel, Maarten Van; Sloot, Ko Van Der; Fischer, Stefan. - : Zenodo, 2016 BASE Show details 9 Pynlpl: V0.7.7 ... Gompel, Maarten Van; Sloot, Ko Van Der; Fischer, Stefan. - : Zenodo, 2016 BASE Show details 10 A framework for (under)specifying dependency syntax without overloading annotators ... Schneider, Nathan; O'Connor, Brendan; Saphra, Naomi. - : arXiv, 2013 BASE Show details

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