LLMs show significant biases in conflict event classification, with open-weight models exhibiting false illegitimation and adapted models showing actor bias and lexical sensitivity, making them unsuitable for unsupervised deployment.
Optimizing Location Extraction, Information Classification, and Visualization With Large Language Models for Humanitarian Crises , url =
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Are LLMs Ready for Conflict Monitoring? Empirical Evidence from West Africa
LLMs show significant biases in conflict event classification, with open-weight models exhibiting false illegitimation and adapted models showing actor bias and lexical sensitivity, making them unsuitable for unsupervised deployment.