Are LLMs Ready for Conflict Monitoring? Empirical Evidence from West Africa
As LLMs enter conflict monitoring, understanding systematic distortions in their outputs is critical for humanitarian accountability. We evaluate four vanilla open-weight models Gemma 3 4B, Llama 3.2 3B, Mistral 7B, and OLMo 2 7B and two domain-adapted models, AfroConfliBERT and AfroConfliLLAMA, on Nigeria and Cameroon conflict-event classification against ACLED, a gold-standard dataset with multi-stage verification. We find a bifurcated divergence in normative directionality. Open-weight models exhibit statistically significant False Illegitimation bias: Gemma misclassifies to 18.29% of legitimate battles as civilian-targeted violence while making zero False Legitimation errors. By contr...
| Authors | Hoffmann Muki, Olukunle Owolabi |
|---|---|
| Primary category | cs.CL |
| Published | 5 May 2026 |
| Last updated at source | 5 May 2026 |
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