Unverified50% confidenceFactExact time
自回归模型将联合概率拆解为逐步条件概率的乘积，通过因果注意力掩码确保每个token只能看到左侧历史信息
1
Sources
50%
Confidence
Long-term
Relevance
7/13/2026
First Seen
Sources
The Rise of Diffusion Language Models: DiffusionGemma Crushes Autoregressive Models in Speed Tests
redditr/GoogleGeminiAI7/11/2026
Related Claims
UnverifiedAutoregressive generative models sample the next token at each step based on the probability distribution of the preceding context; when a repetitive pattern gains a slightly higher probability, it forms a positive feedback loop that leads to repetition degeneration.75% similarUnverified传统自回归推理中，模型每一步只能基于已有上下文预测下一个token，是串行依赖关系74% similarUnverifiedLarge language models use an autoregressive generation mechanism, sampling the next token at each step based solely on a probability distribution, with each token's generation conditioned on all preceding tokens to form a chain of probabilistic dependencies.73% similarUnverified贝叶斯优化基于概率代理模型（通常为高斯过程）建模历史实验结果，在探索与利用之间智能权衡，通常能以更少实验次数找到接近最优的参数配置72% similarUnverifiedEach time a token is generated via a forward pass, the model must go through a complete multi-head attention computation and feed-forward network layers, with the amount of computation determined by the model's parameter scale71% similar
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