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1
Neural reality of argument structure constructions ...
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2
On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems ...
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3
TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction ...
Li, Bai; Rudzicz, Frank. - : arXiv, 2021
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4
Quantifying the Task-Specific Information in Text-Based Classifications ...
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5
An {E}valuation of {D}isentangled {R}epresentation {L}earning for {T}exts ...
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6
How is BERT surprised? Layerwise detection of linguistic anomalies ...
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7
Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech
In: Front Aging Neurosci (2021)
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8
Identification of primary and collateral tracks in stuttered speech
In: LREC 2020 - 12th Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-02959454 ; LREC 2020 - 12th Conference on Language Resources and Evaluation, May 2020, Marseille, France (2020)
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9
Semantic coordinates analysis reveals language changes in the AI field ...
Zhu, Zining; Xu, Yang; Rudzicz, Frank. - : arXiv, 2020
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10
Word class flexibility: A deep contextualized approach ...
Abstract: Word class flexibility refers to the phenomenon whereby a single word form is used across different grammatical categories. Extensive work in linguistic typology has sought to characterize word class flexibility across languages, but quantifying this phenomenon accurately and at scale has been fraught with difficulties. We propose a principled methodology to explore regularity in word class flexibility. Our method builds on recent work in contextualized word embeddings to quantify semantic shift between word classes (e.g., noun-to-verb, verb-to-noun), and we apply this method to 37 languages. We find that contextualized embeddings not only capture human judgment of class variation within words in English, but also uncover shared tendencies in class flexibility across languages. Specifically, we find greater semantic variation when flexible lemmas are used in their dominant word class, supporting the view that word class flexibility is a directional process. Our work highlights the utility of deep ... : To appear in EMNLP 2020 (Long Paper) ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2009.09241
https://arxiv.org/abs/2009.09241
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11
To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection ...
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12
An information theoretic view on selecting linguistic probes ...
Zhu, Zining; Rudzicz, Frank. - : arXiv, 2020
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13
Examining the rhetorical capacities of neural language models ...
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14
A textual analysis of US corporate social responsibility reports
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15
Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power ...
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16
Representation Learning for Discovering Phonemic Tone Contours ...
Li, Bai; Xie, Jing Yi; Rudzicz, Frank. - : arXiv, 2019
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17
Machine learning for MEG during speech tasks
Kostas, Demetres; Pang, Elizabeth W.; Rudzicz, Frank. - : Nature Publishing Group UK, 2019
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18
The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech ...
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19
Detecting cognitive impairments by agreeing on interpretations of linguistic features ...
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20
Deconfounding age effects with fair representation learning when assessing dementia ...
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