Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Shin, Hyungyu"'
Autor:
Kim, Dae Hyun, Shin, Hyungyu, Yadgarova, Shakhnozakhon, Son, Jinho, Subramonyam, Hariharan, Kim, Juho
Clients often partner with AI experts to develop AI applications tailored to their needs. In these partnerships, careful planning and clear communication are critical, as inaccurate or incomplete specifications can result in misaligned model characte
Externí odkaz:
http://arxiv.org/abs/2402.08938
This work investigates large language models (LLMs) as teachable agents for learning by teaching (LBT). LBT with teachable agents helps learners identify knowledge gaps and discover new knowledge. However, teachable agents require expensive programmi
Externí odkaz:
http://arxiv.org/abs/2309.14534
RDF data are used to model knowledge in various areas such as life sciences, Semantic Web, bioinformatics, and social graphs. The size of real RDF data reaches billions of triples. This calls for a framework for efficiently processing RDF data. The c
Externí odkaz:
http://arxiv.org/abs/1506.01973
Publikováno v:
Proceedings of the VLDB Endowment; 20240101, Issue: Preprints p1238-1249, 12p
Autor:
Choi, Yoonseo, Shin, Hyungyu, Monserrat, Toni-Jan Keith, Lee, Nyoungwoo, Park, Jeongeon, Kim, Juho
Publikováno v:
ACM International Conference Proceeding Series; 7/22/2020, p1-4, 4p