Expired60% confidenceFactExact time
Modern large language models are all built on the Decoder-only variant of the Transformer, with parameter counts ranging from billions to trillions.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/4/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/2/2026(expired)
Sources
从零搭建AI Agent：用Python实现对话智能体核心功能
bilibili川府于瑾年7/2/2026
Related Claims
VerifiedLarge language models are based on the Transformer architecture and are trained on massive amounts of text data.78% similarUnverifiedCurrent mainstream large language models generally adopt the Transformer architecture, whose self-attention mechanism has a computational complexity that grows quadratically with sequence length (O(n²)) when processing long contexts.75% similarUnverified大语言模型通常采用仅解码器（Decoder-only）的Transformer变体，通过因果掩码确保每个位置只能关注其之前的token75% similarVerifiedTransformer-based large language models use attention mechanisms to uniformly encode system prompts, user inputs, and externally retrieved content as homogenized token sequences, making it impossible for the model to distinguish trusted instructions from untrusted data at the semantic level.73% similarVerifiedThe root cause of hallucinations in large language models lies in the Transformer architecture's objective of maximizing probability during text generation, rather than prioritizing factual accuracy.73% similar
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