DynamicTOC: Persona-based Table of Contents for Consumption of Long Documents

Anonymous

Paper Link: https://openreview.net/forum?id=4nTcI5gs-DT

Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)

Abstract: Long documents like contracts, financial documents, etc., are often tedious to read through. Linearly consuming (via scrolling or navigation through default table of content) these documents is time-consuming and challenging. These documents are also authored to be consumed by varied entities (referred to as persona in the paper) interested in only certain parts of the document. In this work, we describe DynamicToC, a dynamic table of content-based navigator, to aid in the task of non-linear, persona-based document consumption. DynamicToC highlights sections of interest in the document as per the aspects relevant to different personas. DynamicToC is augmented with short questions to assist the users in understanding underlying content. This uses a novel deep-reinforcement learning technique to generate questions on these persona-clustered paragraphs. Human and automatic evaluations suggest the efficacy of both end-to-end pipeline and different components of DynamicToC.

Copyright Consent Signature (type Name Or NA If Not Transferrable): Sumit Shekhar

Copyright Consent Job Title: Research Scientist

Copyright Consent Name And Address: Adobe Research India