Summary Explorer: Visualizing the State of the Art in Text Summarization
Shahbaz Syed, Tariq Yousef, Khalid Al Khatib, Stefan Jänicke, Martin Potthast
Abstract
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/- Anthology ID:
- 2021.emnlp-demo.22
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Heike Adel, Shuming Shi
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 185–194
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-demo.22
- DOI:
- 10.18653/v1/2021.emnlp-demo.22
- Cite (ACL):
- Shahbaz Syed, Tariq Yousef, Khalid Al Khatib, Stefan Jänicke, and Martin Potthast. 2021. Summary Explorer: Visualizing the State of the Art in Text Summarization. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 185–194, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Summary Explorer: Visualizing the State of the Art in Text Summarization (Syed et al., EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2021.emnlp-demo.22.pdf
- Code
- webis-de/summary-explorer