Unverified50% confidenceFactExact time
The underlying working mechanism of LLMs is to predict the next token.
1
Sources
50%
Confidence
Long-term
Relevance
9/24/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe core capability of modern LLMs lies in 'next token prediction,' generating coherent text through statistical language patterns rather than truly understanding semantics.78% similarVerifiedThe training objective of a Base LLM is to predict the next word, using a paradigm called Autoregressive Language Modeling76% similarUnverifiedLLMs are essentially next-token prediction machines based on statistical patterns, and their output is the text sequence with the highest probability given the context.76% similarUnverifiedLLMs generate code by predicting 'the most likely next token to appear in the current context.'75% similarUnverifiedLLMs generate text in an autoregressive manner, predicting the next token one at a time, with each prediction based on all prior context.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/946679API
curl https://kongchang.com/api/v1/knowledge/claims/946679MCP
get_claim(id=946679)