How does probabilistic decoding control hallucination risk in ChatGPT generation?

Probabilistic decoding adjusts token sampling distributions to balance creativity and factual accuracy, reducing hallucination risk.

ChatGPT generates responses by sampling from a probability distribution over tokens. Decoding strategies like temperature scaling, top-k, and nucleus sampling influence randomness.

Lower temperature and stricter sampling reduce hallucination by favoring high-probability tokens. However, overly deterministic decoding can reduce creativity and expressiveness.

Advanced systems may dynamically adjust decoding parameters based on task type, using more conservative settings for factual queries and more flexible ones for creative tasks.