Unverified50% confidenceFactExact time
A single forward pass means the model only needs to compute the network weights in full once rather than looping autoregressively token by token, giving it a structural advantage in latency and computational resource consumption.
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50%
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Long-term
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10/2/2026
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UnverifiedEach 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 scale75% similarUnverified贝叶斯网络通过有向无环图显式建模变量间的条件依赖关系，适合捕捉因果链条73% similarUnverifiedArchitectures with recurrence can theoretically express iterative algorithms by repeatedly applying the same transformation, whereas fixed-depth feedforward networks have difficulty naturally expressing this type of computation.72% similarUnverifiedThe augmented Lagrangian method explicitly models the inter-layer relationships in predictive coding as a constrained optimization problem, retaining penalty terms while introducing Lagrangian multipliers to satisfy the constraints.71% similarUnverifiedAn autoregressive model requires only one forward pass to generate each token.71% similar
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