  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/
