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Data Whisperer: Efficient Data Selection For Task-Specific LLM Fine-Tuning Via Few-Shot In-Context Learning by ice water is a document available to read on EtoBox.

What is Data Whisperer: Efficient Data Selection For Task-Specific LLM Fine-Tuning Via Few-Shot In-Context Learning about?

The document introduces Data Whisperer, an efficient, training-free method for selecting optimal subsets of data for fine-tuning large language models (LLMs) using few-shot in-context learning. It addresses the inefficiencies of traditional data selection methods by eliminating the need for a separate scoring model, achieving superior performance with reduced computational costs. Comprehensive evaluations demonstrate that Data Whisperer significantly outperforms existing methods, achieving faster selection

Author

ice water

Language

EN