This paper introduces Summary Explorer, a new tool to support the manual inspection of text summarization systems by compiling the outputs of 55~state-of-the-art single document summarization approaches on three benchmark datasets, and visually exploring them during a qualitative assessment. The underlying design of the tool considers three well-known summary quality criteria (coverage, faithfulness, and position bias), encapsulated in a guided assessment based on tailored visualizations. The tool complements existing approaches for locally debugging summarization models and improves upon them. The tool is available at https://tldr.webis.de/
@article{arxiv.2108.01879,
title = {Summary Explorer: Visualizing the State of the Art in Text Summarization},
author = {Shahbaz Syed and Tariq Yousef and Khalid Al-Khatib and Stefan Jänicke and Martin Potthast},
journal= {arXiv preprint arXiv:2108.01879},
year = {2021}
}