CritICL Framework Uses Small Model Failures for Inference-Time Reasoning

CritICL improves reasoning performance by using failure modes from smaller models in a family as in-context guidance for larger models. This approach enables inference-time scaling without the heavy computational overhead of repeated generation or external verification.