SpiralThinker: Latent Reasoning through an Iterative Process with Text-Latent Interleaving

SpiralThinker represents a breakthrough in latent reasoning, addressing the limitations of existing methods that struggle with stable evolution of representations. By employing an iterative process that interleaves implicit and explicit reasoning, it achieves superior performance across mathematical, logical, and commonsense reasoning tasks. The framework's success underscores the critical roles of iteration and alignment, revealing that optimal performance is contingent on dataset-specific configurations. This development not only sets a new benchmark for latent reasoning approaches but also opens avenues for further exploration in AI, emphasizing the need for innovative frameworks that can adaptively enhance reasoning capabilities.