IGA : An Intent-Guided Authoring Assistant
Simeng Sun, Wenlong Zhao, Varun Manjunatha, Rajiv Jain, Vlad Morariu,, Franck Dernoncourt, Balaji Vasan Srinivasan, Mohit Iyyer

TL;DR
IGA is an interactive authoring tool that uses fine-tuned language models to generate and rephrase text based on user-specified rhetorical directives, enhancing controllability in AI-assisted writing.
Contribution
The paper introduces a novel intent-guided writing assistant that leverages fine-tuned language models to generate text according to user-defined tags, enabling more controllable writing assistance.
Findings
IGA produces high-quality, controllable text generation.
Users prefer IGA over baseline methods in creative writing tasks.
Automatic and crowdsourced evaluations confirm IGA's effectiveness.
Abstract
While large-scale pretrained language models have significantly improved writing assistance functionalities such as autocomplete, more complex and controllable writing assistants have yet to be explored. We leverage advances in language modeling to build an interactive writing assistant that generates and rephrases text according to fine-grained author specifications. Users provide input to our Intent-Guided Assistant (IGA) in the form of text interspersed with tags that correspond to specific rhetorical directives (e.g., adding description or contrast, or rephrasing a particular sentence). We fine-tune a language model on a dataset heuristically-labeled with author intent, which allows IGA to fill in these tags with generated text that users can subsequently edit to their liking. A series of automatic and crowdsourced evaluations confirm the quality of IGA's generated outputs, while a…
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Text Readability and Simplification
