Common uncertainty estimation approaches remain as black-boxes without explaining which features have led to the uncertainty of a prediction. We introduce an approach to decompose and visualize the uncertainty of text classifiers at the level of words. We aim to enable a deeper inspection and reasoning about unreliable model behaviours by providing detailed explanations of uncertainties.

Word-Level Uncertainty Estimation for Black-Box Text Classifiers using RNNs

POSTER20: Text Classification, Text Mining and Knowledge Extraction

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COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

Jakob Smedegaard Andersen

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Word-Level Uncertainty Estimation for Black-Box Text Classifiers using RNNs

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