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A_{1}\succ A_{2}) as shown in Figure 2 (left). We do not strictly formalize the measurement function MM, considering that its real-world definitions are various and could range from log-probabilities to other complex scoring mechanisms. This prioritization can be modeled as a directed graph where nodes are instructions or values and edges represent priority relationships (Zhang et al., 2025; Wallace et al., 2025). However, unlike Asimov鈥檚 simple linear hierarchy, these graphs can contain directed cycles (e.g., A1鈮籄2鈮籄3鈮籄
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Diffusion models can be made more efficient and produce better outputs by dynamically allocating compute based on a learned "difficulty" signature, without any retraining.
