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Chen-Hao Dang

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Preprint Aug 2026

SKILLER: Language-Level Reinforcement Learning for Reusable Skill Extraction in Small Language Models

Agent skills represent a standardized format for packaging procedural knowledge and domain expertise, serving within agent harness systems as an essential mechanism to continually constrain a language model's behavior space for repeatable, high-quality task execution. However, because strong closed-source models entail...

Chen-Hao Dang, Siyuan Xiong, Conghui He et al. · 2 citations
#artificial intelligence Preprint Sep 2026

Earth-Agent-Pro: Towards Real-World Full-Chain Earth Observation with Agents

Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare data, perform domain computations, and derive conclusions from runtime evidence. Existing EO agents typically start from supplied observations, while benchmarks typically pr...

Zhu-Tao Lv, Chen-Hao Dang, Yi-Cong Feng et al. · 0 citations

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