Unverified50% confidenceFactExact time
DiffusionGemma使用双向注意力，去掉因果掩码，让每个位置能同时关注序列中所有其他位置，机制与BERT编码器相同
1
Sources
50%
Confidence
Long-term
Relevance
8/28/2026
First Seen
Sources
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Related Claims
UnverifiedDiffusionGemma依赖双向注意力，让前后位置互相照应，这是其生成质量不输自回归的核心机制78% similarUnverifiedDiffusionGemma采用整片并行去噪的生成机制，先铺开256个位置的噪声，然后逐轮迭代，将置信度最高的位置先固定，其余位置重新注入噪声72% similarVerifiedThe self-attention mechanism of the Transformer allows the model to directly compute dependencies between any two positions in a sequence, breaking through the parallelization bottleneck caused by the sequential computation of RNNs/LSTMs.68% similarUnverified自注意力机制允许模型在单次计算中直接建立序列中任意两个位置元素之间的语义依赖关系，解决了长距离依赖问题并支持并行计算68% similarPartially VerifiedThrough the self-attention mechanism, Transformer allows the model to dynamically attend to all other tokens in the sequence when processing each token, while enabling fully parallelized training.67% similar
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