[Seminar] Neural Interface for World Knowledge
호스트: 전병곤 교수 (x1928)
Modern natural language and machine learning problems are increasingly dependent on external world knowledge, and thus how we encode and interact with knowledge data has become very important as well. In this talk, I will discuss different approaches in the literature for handling world knowledge, and in particular, our recent work on creating a memory interface for accessing massive unstructured knowledge data. I will then argue both observed and hypothetical advantages of such a memory-based approach, especially how it can help us to perform more complex interaction with world knowledge including language reasoning.
Minjoon Seo is an Assistant Professor at KAIST Graduate School of AI. He finished his Ph.D. at the University of Washington, advised by Hannaneh Hajishirzi and Ali Farhadi. His research interest is in natural language processing and machine learning, and in particular, how knowledge data can be encoded (e.g. external memory and language model), accessed (e.g. question answering and dialog), and produced (e.g. scientific reasoning). His study was supported by Facebook Fellowship and AI2 Key Scientific Challenges Award. He previously co-organized MRQA 2018, MRQA 2019 and RepL4NLP 2020.
문의: 소프트웨어플랫폼연구실 (02-880-1611)