ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866915895205429248 |
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| author | Ahmad, Raia Abu Upravitelev, Max Usmanova, Aida Solopova, Veronika Rehm, Georg |
| author_facet | Ahmad, Raia Abu Upravitelev, Max Usmanova, Aida Solopova, Veronika Rehm, Georg |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_26449 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims Ahmad, Raia Abu Upravitelev, Max Usmanova, Aida Solopova, Veronika Rehm, Georg Computation and Language 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. |
| title | ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2603.26449 |