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Redundancy and Error Correction in Autoregressive Language Model Learning

Redundancy in language, eg “I am Sam” vs “am Sam”, makes communication robust to errors. Is there a crisp argument for why this error-correction helps in learning auto-regressive language models? The intuition seems right but I’d love to see a formal proof or experiment.

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