Unverified50% confidenceFactExact time
MUM于2021年由谷歌提出，是BERT的继任者，参数量约为BERT的1000倍，支持75种语言的跨语言理解
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50%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
Related Claims
UnverifiedBERT由Google于2018年提出，采用双向编码架构，参数量通常在1亿至3.4亿之间69% similarUnverifiedBERT was released by Google in 2018, employing bidirectional pre-training that randomly masks 15% of words via a masked language model and requires their restoration.65% similarUnverifiedGoogle's Universal Speech Model (USM) supports more than 100 languages.64% similarUnverified谷歌发布的mBERT首次展示了一个模型可以通过共享参数在104种语言上同时进行表示学习，并表现出零样本跨语言迁移能力63% similarVerifiedBERT was introduced by Google in 2018, a pioneering work in pre-trained language models, and was the first to adopt a bidirectional encoder architecture, setting new records on 11 NLP benchmark tests.62% similar
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