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This work proposes SAUCE (Sequential Agent Uncertainty through Consensus Evolution), a lightweight, training-free uncertainty estimator that formulates MAS uncertainty as sequential inference over a latent system-level belief.
Under a matched budget, ResemBrick surpasses existing voxel selectors in perceptual fidelity while uniquely reaching zero floating and zero unstable bricks on unfiltered held-out objects; as a complete pipeline, it attains the best perceptual fidelity among prior brick-construction systems.
This work reports interpretability experiments for a tokenized autoregressive Transformer agent in the Game of Hidden Rules (GOHR), a compact two-rule task in which both hidden rules map object shapes to target buckets, but with different permutations.
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