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This research paper from MediaTek and National Taiwan University challenges the assumption that reasoning chains must be dense and sequential, showing that models can extract answers from sparse, shuffled, and noisy reasoning traces. The findings suggest that answer extraction is robust and order-independent, potentially enabling more efficient, parallelized reasoning generation.