no code implementations • 9 Apr 2024 • Kennedy Edemacu, Xintao Wu
As a result, the sizes of these models have notably expanded in recent years, persuading researchers to adopt the term large language models (LLMs) to characterize the larger-sized PLMs.
no code implementations • 8 Mar 2024 • Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu
In-context learning (ICL) enables large language models (LLMs) to adapt to new tasks by conditioning on demonstrations of question-answer pairs and it has been shown to have comparable performance to costly model retraining and fine-tuning.
no code implementations • 14 Jan 2021 • Kennedy Edemacu, Beakcheol Jang, Jong Wook Kim
Multi-party machine learning is a paradigm in which multiple participants collaboratively train a machine learning model to achieve a common learning objective without sharing their privately owned data.