Unverified50% confidenceFactExact time
Pre-trained language models such as BERT learn to capture fine-grained contextual word meanings through masked language modeling tasks.
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50%
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Long-term
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9/28/2026
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UnverifiedBERT 的掩码语言模型随机遮蔽输入文本中 15% 的词元并要求模型预测原词76% similarUnverifiedBERT 在英文维基百科和 BookCorpus（共约 33 亿词）上进行了掩码语言模型（MLM）预训练75% similarVerifiedModern multilingual large models establish language-agnostic semantic representations during the pre-training phase, building cross-lingual semantic alignment in high-dimensional vector space through joint training on massive multilingual corpora.75% similarVerifiedLLMs acquire language capabilities by performing unsupervised pre-training on massive text corpora (predicting the next token).74% similarUnverifiedLarge language models are trained on massive corpora that may already contain extensive mathematical literature, problem-solving processes, and even answers to similar problems.73% similar
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