Expired70% confidenceFactExact time
Large language models are autoregressive generation models where each output step depends on the preceding context.
2
Sources
70%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
AI Agent Core Architecture Breakdown: From Concept to Enterprise-Grade Intelligent Agent Development
bilibili编程奇遇6/12/2026
Related Claims
UnverifiedLarge language models predict the next token one at a time through an autoregressive generation mechanism, and are naturally inclined to generate more complete rather than more concise code.80% similarUnverifiedLanguage models work through autoregressive generation: given all preceding tokens, they predict the probability distribution of the next token and sample an output.78% similarUnverifiedLarge language models generate text in an autoregressive manner, where the production of each token depends on the context formed by all preceding tokens, following the chain rule of probability.77% similarUnverifiedModern large language models generate code in an auto-regressive manner, predicting the next token each time by referencing only the existing context.77% similarUnverified自回归多模态模型借鉴语言模型的token预测机制，在理解复杂文字指令和保持角色一致性方面更具优势76% similar
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