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

Next in our spring seminar series, we welcome Dr. Nancy Chen, Infocomm Research (I2R), A*STAR (Agency for Science, Technology, and Research), Singapore.

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.

Those who cannot attend in-person are welcome to tune in virtually through Webex: https://utsa.webex.com/utsa/j.php?MTID=m568fe3d73989cb26d676f896e952c3c0.