Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages

• URL: http://arxiv.org/abs/2511.14598v1
• Date: Tue, 18 Nov 2025 15:39:48 GMT
• Title: Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages
• Authors: Noam Dahan, Omer Kidron, Gabriel Stanovsky,
• Abstract summary: We present a novel method for collecting naturally occurring summaries via Front-Page Teasers.<n>We show that this phenomenon is common across seven diverse languages and supports multi-document summarization.<n>We apply this process to a Hebrew newspaper title, producing HEBTEASESUM, the first dedicated multi-document summarization dataset in Hebrew.
• Score: 16.066443926940753
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: High quality summarization data remains scarce in under-represented languages. However, historical newspapers, made available through recent digitization efforts, offer an abundant source of untapped, naturally annotated data. In this work, we present a novel method for collecting naturally occurring summaries via Front-Page Teasers, where editors summarize full length articles. We show that this phenomenon is common across seven diverse languages and supports multi-document summarization. To scale data collection, we develop an automatic process, suited to varying linguistic resource levels. Finally, we apply this process to a Hebrew newspaper title, producing HEBTEASESUM, the first dedicated multi-document summarization dataset in Hebrew.

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