CCQA: Generating Question from Solution Can Improve Inference-Time Reasoning in SLMs
CCQA is a method for improving how Small Language Models (SLMs) reason during inference. It works by generating a new question from each candidate answer or reasoning path produced by the model and then selecting the solution whose generated question most closely matches the original input question. This technique helps SLMs perform better, especially when standard voting methods fail.