ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims

Raia Abu Ahmad, Max Upravitelev, Aida Usmanova, Veronika Solopova, Georg Rehm
3/27/2026
cs.CL

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Abstract

Automatically verifying climate-related claims against scientific literature is a challenging task, complicated by the specialised nature of scholarly evidence and the diversity of rhetorical strategies underlying climate disinformation. ClimateCheck 2026 is the second iteration of a shared task addressing this challenge, expanding on the 2025 edition with tripled training data and a new disinformation narrative classification task. Running from January to February 2026 on the CodaBench platform, the competition attracted 20 registered participants and 8 leaderboard submissions, with systems combining dense retrieval pipelines, cross-encoder ensembles, and large language models with structured hierarchical reasoning. In addition to standard evaluation metrics (Recall@K and Binary Preference), we adapt an automated framework to assess retrieval quality under incomplete annotations, exposing systematic biases in how conventional metrics rank systems. A cross-task analysis further reveals that not all climate disinformation is equally verifiable, potentially implicating how future fact-checking systems should be designed.

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Cite this paper

@article{ahmad2026climatecheck,
  title  = {ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims},
  author = {Raia Abu Ahmad and Max Upravitelev and Aida Usmanova and Veronika Solopova and Georg Rehm},
  year   = {2026},
  eprint = {2603.26449},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.26449v1}
}

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