mlsanityData to 7 Oct 2026

Klexikon: A German Dataset for Joint Summarization and Simplification

arXiv 2201.07198 ↗First posted 18 Jan 2022cs.CLcited by 15

Not on the map. Why?

Abstract (arXiv)

Traditionally, Text Simplification is treated as a monolingual translation task where sentences between source texts and their simplified counterparts are aligned for training. However, especially for longer input documents, summarizing the text (or dropping less relevant content altogether) plays an important role in the simplification process, which is currently not reflected in existing datasets. Simultaneously, resources for non-English languages are scarce in general and prohibitive for training new solutions. To tackle this problem, we pose core requirements for a system that can jointly summarize and simplify long source documents. We further describe the creation of a new dataset for joint Text Simplification and Summarization based on German Wikipedia and the German children's lexicon "Klexikon", consisting of almost 2900 documents. We release a document-aligned version that particularly highlights the summarization aspect, and provide statistical evidence that this resource is well suited to simplification as well. Code and data are available on Github: https://github.com/dennlinger/klexikon

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 6 of its 49 references that are in the map. First posted on arXiv 18 Jan 2022.

Builds on

6 of 49 references.

References · 6

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2016SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documentscited by 245
  3. 2019Hierarchical Transformers for Multi-Document Summarizationcited by 132
  4. 2020Neural CRF Model for Sentence Alignment in Text Simplificationcited by 106
  5. 2019A Corpus for Automatic Readability Assessment and Text Simplification of Germancited by 18
  6. 2017A Semantic Relevance Based Neural Network for Text Summarization and Text Simplificationcited by 3

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 7; 2024: 4; 2025: 2.

15 papers.

Sort:

By area: