Harini Eavani

Few-Shot NLG with Pre-Trained Language Model

2019 · arXiv (Cornell University)

Neural-based end-to-end approaches to natural language generation (NLG) from structured data or knowledge are data-hungry, making their adoption for real-world applications difficult with limited data. In this work, we propose the new task of \textit{few-shot …