Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation
We present QIMMA, a quality-assured Arabic LLM leaderboard that places systematic benchmark validation at its core. Rather than aggregating existing resources as-is, QIMMA applies a multi-model assessment pipeline combining automated LLM judgment with human review to surface and resolve systematic quality issues in well-established Arabic benchmarks before evaluation. The result is a curated, multi-domain, multi-task evaluation suite of over 52k samples, grounded predominantly in native Arabic content; code evaluation tasks are the sole exception, as they are inherently language-agnostic. Transparent implementation via LightEval, EvalPlus and public release of per-sample inference outputs...
| Authors | Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai et al. |
|---|---|
| Primary category | cs.CL |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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