no code implementations • 30 Jan 2024 • Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi
Recently, there has been an increasing interest in ensuring fairness on GNNs, but all of them are under the assumption that the training and testing data are under the same distribution, i. e., training data and testing data are from the same graph.
no code implementations • 9 Nov 2022 • Yujie Xing, Jon Atle Gulla
In this paper, we focus on an essential component of multi-turn generation-based conversational agents: context attention distribution, i. e. how systems distribute their attention on dialogue's context.
no code implementations • Findings (NAACL) 2022 • Yujie Xing, Jinglun Cai, Nils Barlaug, Peng Liu, Jon Atle Gulla
Furthermore, we propose Domain-specific Frequency (DF), a novel word-level importance weight that measures the relative importance of a word for a specific corpus compared to other corpora.
no code implementations • WS 2018 • Yujie Xing, Raquel Fernández
Stylistic variation is critical to render the utterances generated by conversational agents natural and engaging.