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arXiv Machine Learning By Zhiyuan Li

The Optimal Sample Complexity of Learning Autoregressive Chain-of-Thought

Read the original on arXiv Machine Learning →

arXiv:2607. 07423v1 Announce Type: new Abstract: We prove that, in the realizable PAC setting, the sample complexity of exact-trace learning for full autoregressive Chain-of-Thought traces is upper bounded by the standard multiclass rate of the local next-token class, where this rate is governed by the Daniely--Shalev-Shwartz dimension.

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