Middle-removal truncation destroys the answer in most samples; when only distractors are removed, shorter context never hurts and sometimes improves small models.
MRCR dataset.https://huggingface.co/datasets/openai/mrcr, 2025
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Distractor-Aware Truncation: Disentangling Context-Length Effects from Signal Loss in Long-Context LLM Benchmarks
Middle-removal truncation destroys the answer in most samples; when only distractors are removed, shorter context never hurts and sometimes improves small models.