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

Noam Dahan; Omer Kidron; Gabriel Stanovsky

doi:10.18653/v1/2026.findings-eacl.278

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

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026
Publisher	Association for Computational Linguistics (ACL)
Pages	5260-5273
Number of pages	14
ISBN (Electronic)	9798891763869
DOIs	https://doi.org/10.18653/v1/2026.findings-eacl.278
State	Published - 2026
Event	19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026 - Rabat, Morocco Duration: 24 Mar 2026 → 29 Mar 2026

Publication series

Name	19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026

Conference

Conference	19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026
Country/Territory	Morocco
City	Rabat
Period	24/03/26 → 29/03/26

Bibliographical note

Publisher Copyright:
©2026 Association for Computational Linguistics.

Access to Document

10.18653/v1/2026.findings-eacl.278

Cite this

Dahan, N., Kidron, O., & Stanovsky, G. (2026). Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. In 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026 (pp. 5260-5273). (19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2026.findings-eacl.278

Dahan, Noam ; Kidron, Omer ; Stanovsky, Gabriel. / Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026. Association for Computational Linguistics (ACL), 2026. pp. 5260-5273 (19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026).

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title = "Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages",

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.",

author = "Noam Dahan and Omer Kidron and Gabriel Stanovsky",

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year = "2026",

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series = "19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026",

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Dahan, N, Kidron, O & Stanovsky, G 2026, Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. in 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026. 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026, Association for Computational Linguistics (ACL), pp. 5260-5273, 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026, Rabat, Morocco, 24/03/26. https://doi.org/10.18653/v1/2026.findings-eacl.278

Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. / Dahan, Noam; Kidron, Omer ; Stanovsky, Gabriel.
19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026. Association for Computational Linguistics (ACL), 2026. p. 5260-5273 (19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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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Dahan N, Kidron O , Stanovsky G. Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. In 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026. Association for Computational Linguistics (ACL). 2026. p. 5260-5273. (19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026). doi: 10.18653/v1/2026.findings-eacl.278

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

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