Text-to-Text Pre-Training for Data-to-Text Tasks [article]

Mihir Kale, Abhinav Rastogi
2021 arXiv   pre-print
We study the pre-train + fine-tune strategy for data-to-text tasks. Our experiments indicate that text-to-text pre-training in the form of T5, enables simple, end-to-end transformer based models to outperform pipelined neural architectures tailored for data-to-text generation, as well as alternative language model based pre-training techniques such as BERT and GPT-2. Importantly, T5 pre-training leads to better generalization, as evidenced by large improvements on out-of-domain test sets. We
more » ... e our work serves as a useful baseline for future research, as transfer learning becomes ever more prevalent for data-to-text tasks.
arXiv:2005.10433v3 fatcat:cb7xh7zfg5hqnafca6q5etn6my