Reasoning language models extract answers from sparse, order-shuffled chain-of-thought traces with little accuracy loss.
arXiv preprint arXiv:2305.14967 , year=
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Rethinking Dense Sequential Chains: Reasoning Language Models Can Extract Answers from Sparse, Order-Shuffling Chain-of-Thoughts
Reasoning language models extract answers from sparse, order-shuffled chain-of-thought traces with little accuracy loss.