mlsanityData to 14 Oct 2026

SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

arXiv 2604.06817 ↗First posted 8 Apr 2026cs.CLcited by 1

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Abstract (arXiv)

We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labeled with the presence of polarization, polarization type, and polarization manifestation. Participants were asked to predict labels in three sub-tasks: (1) detecting the presence of polarization, (2) identifying the type of polarization, and (3) recognizing the polarization manifestation. The three tasks attracted over 1,000 participants worldwide and more than 10k submission on Codabench. We received final submissions from 67 teams and 73 system description papers. We report the baseline results and analyze the performance of the best-performing systems, highlighting the most common approaches and the most effective methods across different subtasks and languages. The dataset of this task is publicly available.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 91 references that are in the map. First posted on arXiv 8 Apr 2026.

Builds on

11 of 91 references.

References · 11

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  6. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
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  10. 2025POLAR: A Benchmark for Multilingual, Multicultural, and Multi-Event Online Polarizationcited by 4
  11. 2025EncouRAGe: Evaluating RAG Local, Fast, and Reliablecited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detectioncited by 0