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cs.CL2024
FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only
He Zhu, Junyou Su, Tianle Lun +4
Instruction fine-tuning stands as a crucial advancement in leveraging large language models (LLMs) for enhanced task performance. However, the annotation of instruction datasets ha…
cs.CL2024★ 4 cited
PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval
He Zhu, Wenjia Zhang, Nuoxian Huang +9
In the field of urban planning, general-purpose large language models often struggle to meet the specific needs of planners. Tasks like generating urban planning texts, retrieving…