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Chain of Thought in Transformers for Parity by bhzk69sbfz is a document available to read on EtoBox.

What is Chain of Thought in Transformers for Parity about?

This paper presents a theoretical analysis of training transformers to solve the k-parity problem using chain-of-thought (CoT) reasoning. It establishes that incorporating intermediate states into the loss function allows the model to learn parity efficiently, either through teacher forcing or by using augmented data for self-consistency checks. The findings highlight the importance of task decomposition and stepwise reasoning in enhancing the performance of transformers on complex problems.

Author

bhzk69sbfz

Language

EN