Computer Science

A Computational Analysis of Vagueness in Revisions of Instructional Texts

A. Debnath and M. Roth

This research by Alok Debnath and Michael Roth dives into the intricacies of vagueness in instructional texts from the WikiHowToImprove dataset. By analyzing edits involving vagueness and developing a novel neural model to enhance clarity in instructions, they demonstrate significant advancements over existing techniques. Tune in to discover these insightful findings!

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Playback language: English

Index

Abstract

This paper analyzes vagueness in revisions of instructional texts from the WikiHowToImprove dataset. The authors extract and analyze edits involving vagueness, focusing on changes in the main verb. They develop a neural model for a pairwise ranking task to distinguish between vague and clarified instructions, showing improvements over existing baselines.

Publisher

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop

Published On

Apr 19, 2021

Authors

Alok Debnath, Michael Roth

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