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The paper introduces H EAVY S KILL, a framework that enhances large language models (LLMs) by internalizing heavy thinking as an inner skill to improve complex reasoning tasks. It proposes a two-stage workflow of parallel reasoning followed by sequential deliberation, which consistently outperforms traditional strategies and allows for iterative refinement of reasoning paths. The study demonstrates that this approach can be optimized through reinforcement learning, leading to self-evolving LLMs capable of e
- Author
- khietdmca
- Language
- EN