In-context learning (ICL) in large language models (LLMs) is a cutting-edge subset of machine learning that uses input-output examples to adapt to new tasks without changing the base model architecture. This methodology has revolutionized how these models manage various tasks by learning from example data during the inference process. However, the current setup, referred to…
