Unverified50% confidenceFactExact time
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
1
Sources
50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
Unverified大语言模型从自回归预测转向强化学习驱动的推理增强（如Chain-of-Thought推理链、Process Reward Model过程奖励模型）81% similarVerifiedThe essence of large language models is learning the conditional probability distribution of what the next word is given the preceding text78% similarUnverifiedThe tool-calling mechanism allows large language models to dynamically invoke external functions during inference, representing a fundamental leap from language models to action models.77% similarUnverified语言的语法结构越简单、惯用模式越统一，大模型在每一步预测中面临的困惑度越低，生成正确序列的概率越高77% similarUnverifiedLarge 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.77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/575559API
curl https://kongchang.com/api/v1/knowledge/claims/575559MCP
get_claim(id=575559)