Unverified50% confidenceFactExact time
The autoregressive generation mechanism of traditional LLMs determines that they predict token by token in a forward direction, lacking a natural ability to look back.
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9/17/2026
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VerifiedThe root cause of LLM hallucination lies in the autoregressive generation mechanism—the model predicts the next Token based on a probability distribution rather than genuine logical reasoning.79% similarUnverifiedLLM 的输出非确定性根源于自回归生成机制，即使输入相同，Temperature、Top-p 等采样参数也会导致不同输出71% similarUnverifiedThe core idea of ReAct is to have LLMs perform explicit reasoning before generating actions, and to feed execution results back to the model as observations to form a closed loop.71% similarUnverifiedThe core generation mechanism of LLMs is: given all preceding tokens, predict the probability distribution of the next token.70% similarPartially VerifiedLLMs use an autoregressive generation mechanism, sampling the next token at each step based solely on a probability distribution.70% similar
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