Decoding

Contrastive Decoding in Large Language Models: How Comparing Expert and Amateur Logits Suppresses Hallucination and Reasoning Errors

Contrastive Decoding in Large Language Models: How Comparing Expert and Amateur Logits Suppresses Hallucination and Reasoning Errors Autoregressive large language models operate by predicting the conditional probability distribution of the next token given a sequence of preceding tokens. However, translating these continuous probability vectors into coherent, factual, and logically sound sequences remains one of the fundamental challenges of modern natural language processing. Traditional deco