David Kauchak


2020

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AutoMeTS: The Autocomplete for Medical Text Simplification
Hoang Van | David Kauchak | Gondy Leroy
Proceedings of the 28th International Conference on Computational Linguistics

The goal of text simplification (TS) is to transform difficult text into a version that is easier to understand and more broadly accessible to a wide variety of readers. In some domains, such as healthcare, fully automated approaches cannot be used since information must be accurately preserved. Instead, semi-automated approaches can be used that assist a human writer in simplifying text faster and at a higher quality. In this paper, we examine the application of autocomplete to text simplification in the medical domain. We introduce a new parallel medical data set consisting of aligned English Wikipedia with Simple English Wikipedia sentences and examine the application of pretrained neural language models (PNLMs) on this dataset. We compare four PNLMs (BERT, RoBERTa, XLNet, and GPT-2), and show how the additional context of the sentence to be simplified can be incorporated to achieve better results (6.17% absolute improvement over the best individual model). We also introduce an ensemble model that combines the four PNLMs and outperforms the best individual model by 2.1%, resulting in an overall word prediction accuracy of 64.52%.

2016

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Pomona at SemEval-2016 Task 11: Predicting Word Complexity Based on Corpus Frequency
David Kauchak
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2014

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Learning a Lexical Simplifier Using Wikipedia
Colby Horn | Cathryn Manduca | David Kauchak
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2013

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Sentence Simplification as Tree Transduction
Dan Feblowitz | David Kauchak
Proceedings of the Second Workshop on Predicting and Improving Text Readability for Target Reader Populations

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Improving Text Simplification Language Modeling Using Unsimplified Text Data
David Kauchak
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2011

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Learning to Simplify Sentences Using Wikipedia
Will Coster | David Kauchak
Proceedings of the Workshop on Monolingual Text-To-Text Generation

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Simple English Wikipedia: A New Text Simplification Task
William Coster | David Kauchak
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2006

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Paraphrasing for Automatic Evaluation
David Kauchak | Regina Barzilay
Proceedings of the Human Language Technology Conference of the NAACL, Main Conference

2005

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Feature-Based Segmentation of Narrative Documents
David Kauchak | Francine Chen
Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing