Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Park, Hancheol"'
Recent language models have shown remarkable performance on natural language understanding (NLU) tasks. However, they are often sub-optimal when faced with ambiguous samples that can be interpreted in multiple ways, over-confidently predicting a sing
Externí odkaz:
http://arxiv.org/abs/2406.09719
Autor:
Park, Hancheol, Park, Jong C.
Natural language understanding (NLU) tasks face a non-trivial amount of ambiguous samples where veracity of their labels is debatable among annotators. NLU models should thus account for such ambiguity, but they approximate the human opinion distribu
Externí odkaz:
http://arxiv.org/abs/2306.07061
Autor:
Kim, Bo-Kyeong, Kang, Jaemin, Seo, Daeun, Park, Hancheol, Choi, Shinkook, Song, Hyoung-Kyu, Kim, Hyungshin, Lim, Sungsu
Virtual humans have gained considerable attention in numerous industries, e.g., entertainment and e-commerce. As a core technology, synthesizing photorealistic face frames from target speech and facial identity has been actively studied with generati
Externí odkaz:
http://arxiv.org/abs/2304.00471
Pruning effectively compresses overparameterized models. Despite the success of pruning methods for discriminative models, applying them for generative models has been relatively rarely approached. This study conducts structured pruning on U-Net gene
Externí odkaz:
http://arxiv.org/abs/2206.14658
Publikováno v:
In Data & Knowledge Engineering September 2019 123
Publikováno v:
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computation. :650-657
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
2016 International Conference on Big Data & Smart Computing (BigComp); 2016, p353-356, 4p
Publikováno v:
2016 International Conference on Big Data & Smart Computing (BigComp); 2016, p199-206, 8p