no code implementations • NAACL (Emoji) 2022 • Yunhe Feng, Cheng Guo, Bingbing Wen, Peng Sun, Yufei Yue, Dingwen Tao
This paper proposes EmojiCloud, an open-source Python-based emoji cloud visualization tool, to generate a quick and straightforward understanding of emojis from the perspective of frequency and importance.
no code implementations • 21 Dec 2023 • Bingbing Wen, Zhengyuan Yang, JianFeng Wang, Zhe Gan, Bill Howe, Lijuan Wang
In this paper, we build a visual dialogue dataset, named InfoVisDial, which provides rich informative answers in each round even with external knowledge related to the visual content.
no code implementations • 30 Nov 2023 • Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi, Yalin Wang
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset.
no code implementations • 17 Aug 2022 • Bingbing Wen, Xiaoning Bu, Chirag Shah
To the best of our knowledge, this is the first framework for explainable conversational recommendation on real-world datasets.
no code implementations • 17 Aug 2022 • Bingbing Wen, Yunhe Feng, Yongfeng Zhang, Chirag Shah
Current explanation generation models are found to exaggerate certain emotions without accurately capturing the underlying tone or the meaning.