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Skills equip LLM agents with professional knowledge and guidance to complete long-horizon and complex tasks. Although skills have been widely adopted in recent agent paradigms and harnesses, how to synthesize reliable training data and how to train agents for skill use remain underexplored. In this work, we propose Ski...
Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLMs) being highly adept in using natural language, they achieve strong performance, yet not perfect, in informal mathematical reasoning. Restraining LLMs to informal reas...
The results show that improving IF in LRMs can significantly enhance privacy, suggesting a promising direction for future privacy-aware LRMs, and introduces an SFT dataset that teaches models to follow general instructions throughout their reasoning process.
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