Unverified50% confidenceFactExact time
BERT and its successor models produce context-aware dynamic vectors, where the same word receives different vector representations in different sentences.
1
Sources
50%
Confidence
Long-term
Relevance
7/24/2026
First Seen
Sources
Spring AI实战：ChatModel到RAG应用开发完整指南
Related Claims
Unverified在BERT时代，词嵌入进化为上下文相关的动态表示，同一个词在不同句子中会获得不同的向量表示75% similarUnverifiedEven with the same model, processing the same prompt at different times or in different conversational contexts can produce outputs with significant quality variation, which is known in the industry as model output instability or the variance problem.66% similarUnverifiedBERT通过掩码语言模型（MLM）任务同时利用上下文的左侧和右侧信息65% similarUnverifiedBERT类模型在意图识别、情感分析、命名实体识别等判别式任务上具有优势，专注于理解而非生成63% similar
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