no code implementations • COLING 2022 • Liang Li, Ruiying Geng, Bowen Li, Can Ma, Yinliang Yue, Binhua Li, Yongbin Li
Most graph-to-text works are built on the encoder-decoder framework with cross-attention mechanism.
1 code implementation • 22 Nov 2021 • Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao
The core objective of modelling recommender systems from implicit feedback is to maximize the positive sample score $s_p$ and minimize the negative sample score $s_n$, which can usually be summarized into two paradigms: the pointwise and the pairwise.
1 code implementation • ACL 2021 • Liang Li, Can Ma, Yinliang Yue, Dayong Hu
However, it is hard for a vanilla encoder to capture these.
Ranked #1 on Table-to-Text Generation on RotoWire
no code implementations • 15 Oct 2020 • Liang Li, Can Ma, Yinliang Yue, Linjun Shou, Dayong Hu
Secondly, the target texts in training dataset may contain redundant information or facts do not exist in the input tables.
no code implementations • 10 Jul 2020 • Xugong Qin, Yu Zhou, Dayan Wu, Yinliang Yue, Weiping Wang
Accurate detection of multi-oriented text with large variations of scales, orientations, and aspect ratios is of great significance.