mlsanityData to 14 Oct 2026

Swiss4Arg: A Parallel Dataset for Multilingual Argument Mining across Swiss National Languages

arXiv 2610.17894 ↗First posted 13 Oct 2026cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

We present Swiss4Arg, a multilingual dataset for argument mining based on official Swiss voting brochures, covering all four national languages: German, French, Italian, and Romansh (a Romance minority language exclusively spoken in Switzerland). The brochures contain explicitly formulated arguments systematically organized into pro and con sections, resulting in a cross-lingually aligned resource with balanced argumentative stance. We create a dataset that comprises 53 federal voting issues collected between 2019 and 2025, annotated for argument components (major claims, claims, premises, and non-argumentative units) and relations (support and attack) by three native speakers per language. Inter-annotator agreement (Krippendorff's alpha) reaches 0.548 for component classification and 0.623 for relation and target classification, computed jointly across all annotators on the parallel data. We release both adjudicated labels and individual annotator annotations, enabling analyses of disagreement and cross-linguistic variation, and provide baseline results using GPT-5.4 and SwissBERT. Swiss4Arg establishes a novel benchmark for multilingual argument mining, with a particular focus on cross-lingual comparability and low-resource settings such as Romansh. The dataset and code are publicly available at https://anonymous-hf.up.railway.app/a/gozw0nion72y/ (HuggingFace) and https://anonymous.4open.science/r/MultiVote-03BD/ (GitHub).

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 37 references that are in the map. First posted on arXiv 13 Oct 2026.

Builds on

15 of 37 references.

References · 15

  1. 2016Parsing Argumentation Structures in Persuasive Essayscited by 101
  2. 2024Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classificationcited by 70
  3. 2020X-Stance: A Multilingual Multi-Target Dataset for Stance Detectioncited by 43
  4. 2025BOUQuET: dataset, Benchmark and Open initiative for Universal Quality Evaluation in Translationcited by 22
  5. 2020Multilingual Argument Mining: Datasets and Analysiscited by 20
  6. 2018Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!cited by 16
  7. 2025SwiLTra-Bench: The Swiss Legal Translation Benchmarkcited by 11
  8. 2025Do BERT-Like Bidirectional Models Still Perform Better on Text Classification in the Era of LLMs?cited by 10
  9. 2023SwissBERT: The Multilingual Language Model for Switzerlandcited by 9
  10. 2020A Corpus for Argumentative Writing Support in Germancited by 7
  11. 2024Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniquescited by 7
  12. 2021Traditional Machine Learning and Deep Learning Models for Argumentation Mining in Russian Textscited by 3
3 more
  1. 2025AMELIA: A Family of Multi-task End-to-end Language Models for Argumentationcited by 3
  2. 2025SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documentscited by 2
  3. 2025Winning with Less for Low Resource Languages: Advantage of Cross-Lingual English_Persian Argument Mining Model over LLM Augmentationcited by 1

Built on by

Not cited yet.