Dongyeop Kang


I am a postdoctoral scholar at University of California, Berkeley, under Marti A. Hearst. I obtained my Ph.D. in the Language Technologies Institute of the School of Computer Science at Carnegie Mellon University, under Eduard Hovy. I interned at Facebook AI, Allen Institute for AI (AI2), and Microsoft Research. My Ph.D. study has been supported by Allen Institute for AI (AI2) Fellowship, CMU Presidential Fellowship, and ILJU Graduate Fellowship. In the middle of my study, I completed my alternative military service in South Korea at Naver Labs and KAIST Institute. Before joining CMU, I obtained my BS and MS in Computer Science Engineering at KAIST, Korea.


dongyeopk@berkeley.edu


I'm interested in building human-like language generation systems. Natural language generation (NLG) is a key component of many language applications such as dialogue systems, question answering systems, and textual summarization. However, they are yet far behind human-like or human-level generation. This is because a multitude of implicit information is NOT explicitly obvious on the surface. We call the kinds of information as facets, that are reflected in variations of a language, such as external knowledge, intents, interpersonal information, and more. To generate human-like utterances, appropriate modeling of these facets is necessary, and the system needs to be effectively guided by them. Based on Halliday’s Systemic Functional Linguistics (SFL) theory (1978), my Ph.D. thesis focuses on three facet groups; knowledge, structure, and style, and presents effective computational methods for handling each facet in a wide range of generation tasks. During my postdoc, as the intersection of NLG and human-computer interaction, I develop human-machine collaborative language technologies in a mixed-initiative way.

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Last updated in June 2020