most citedUPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2023★ 2 cited

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Daixuan Cheng, Shaohan Huang, Junyu Bi +7

Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generaliza…