Neural Language Generation: From Self-Supervised Representation Learning to Multimodal Contextualization

Dr. Nancy Chen

Infocomm Research (I2R), A*STAR (Agency for Science, Technology, and Research), Singapore

Wednesday, April 5, 2023

9AM – 10AM CST

WebEx: https://utsa.webex.com/utsa/j.php?MTID=m66139b13650b563509afee98c46142e9

Abstract:

The recent rapid advancements of neural language models have awed both domain experts and laymen alike. Such language models can fuel many natural language generation applications, including summarization, conversational agents, and machine translation. In this talk, we will illustrate how to harness the capabilities of these language models from a research perspective to address on-going technical challenges. In particular, we will delve into four research themes: scalable data augmentation, factually consistent generation, controllable neural modelling, and multimodal contextualization.