How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?

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Abstract

This paper presents a rigorous internal analysis of <strong>latent reasoning</strong> methods (e.g., Coconut, CODI, CoLaR, SIM-CoT) that perform multi-step computation in continuous hidden spaces. The authors investigate whether these models truly "think" or merely exploit shortcuts, while also evaluating the "Breadth-First Search (BFS)" hypothesis in latent space.

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