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BehaviorFormer: Discovering Behavioral Patterns via Clusterable Next-Token Prediction
Discovering behavioral patterns in open-ended games is challenging due to the lack of clear objectives or ground-truth annotations. In this work, we extend a next-token prediction Transformer with the deep clustering algorithm DCSS to learn meaningful representations with well-separated clusters. In
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