AI RESEARCH
Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
arXiv CS.CL
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ArXi:2603.13201v1 Announce Type: new Instruction Tuning (IT) has been proven to be an effective approach to unlock the powerful capabilities of large language models (LLMs). Recent studies indicate that excessive IT data can degrade LLMs performance, while carefully selecting a small subset of high-quality IT data can significantly enhance their capabilities. Therefore, identifying the most efficient subset data from the IT dataset to effectively develop either specific or general abilities in LLMs has become a critical challenge.