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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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Quantifying the Task-Specific Information in Text-Based Classifications ...
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Abstract:
Recently, neural natural language models have attained state-of-the-art performance on a wide variety of tasks, but the high performance can result from superficial, surface-level cues (Bender and Koller, 2020; Niven and Kao, 2020). These surface cues, as the ``shortcuts'' inherent in the datasets, do not contribute to the *task-specific information* (TSI) of the classification tasks. While it is essential to look at the model performance, it is also important to understand the datasets. In this paper, we consider this question: Apart from the information introduced by the shortcut features, how much task-specific information is required to classify a dataset? We formulate this quantity in an information-theoretic framework. While this quantity is hard to compute, we approximate it with a fast and stable method. TSI quantifies the amount of linguistic knowledge modulo a set of predefined shortcuts -- that contributes to classifying a sample from each dataset. This framework allows us to compare across ...
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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.2110.08931 https://arxiv.org/abs/2110.08931
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How is BERT surprised? Layerwise detection of linguistic anomalies ...
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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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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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Dropout during inference as a model for neurological degeneration in an image captioning network ...
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Predicting health inspection results from online restaurant reviews ...
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