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On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems ...
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TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction ...
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Abstract:
Eye movement data during reading is a useful source of information for understanding language comprehension processes. In this paper, we describe our submission to the CMCL 2021 shared task on predicting human reading patterns. Our model uses RoBERTa with a regression layer to predict 5 eye-tracking features. We train the model in two stages: we first fine-tune on the Provo corpus (another eye-tracking dataset), then fine-tune on the task data. We compare different Transformer models and apply ensembling methods to improve the performance. Our final submission achieves a MAE score of 3.929, ranking 3rd place out of 13 teams that participated in this shared task. ... : Cognitive Modeling and Computational Linguistics Workshop (CMCL) at NAACL 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2104.07244 https://arxiv.org/abs/2104.07244
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Quantifying the Task-Specific Information in Text-Based Classifications ...
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An {E}valuation of {D}isentangled {R}epresentation {L}earning for {T}exts ...
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How is BERT surprised? Layerwise detection of linguistic anomalies ...
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Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech
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In: Front Aging Neurosci (2021)
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Identification of primary and collateral tracks in stuttered speech
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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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Semantic coordinates analysis reveals language changes in the AI field ...
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To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection ...
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An information theoretic view on selecting linguistic probes ...
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Examining the rhetorical capacities of neural language models ...
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A textual analysis of US corporate social responsibility reports
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Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power ...
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Representation Learning for Discovering Phonemic Tone Contours ...
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The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech ...
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Detecting cognitive impairments by agreeing on interpretations of linguistic features ...
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Deconfounding age effects with fair representation learning when assessing dementia ...
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