Unverified50% confidenceFactExact time
主流大语言模型基于Transformer架构，通过预训练将知识压缩进数十亿乃至数千亿的模型权重中
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
Getting Started with LangChain: LLM Invocation, Agent Practice, and Environment Setup Guide
bilibiliAI大模型小将7/10/2026
Related Claims
UnverifiedModern large language models are based on the Transformer architecture and generate text by predicting the probability distribution of the next token, with the training objective of minimizing cross-entropy loss77% similarUnverifiedThe facts absorbed by large language models during the pre-training phase are encoded in a distributed manner across billions of parameters, with a single fact diffused across the activation patterns of hundreds or even thousands of neurons76% similarVerifiedLarge language models do not store raw text in the traditional sense during training; instead, they encode statistical patterns into billions of parameters through the backpropagation algorithm.75% similar
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