2 code implementations • COLING (TextGraphs) 2020 • Weibin Li, Yuxiang Lu, Zhengjie Huang, Weiyue Su, Jiaxiang Liu, Shikun Feng, Yu Sun
To address this problem, we use a pre-trained language model to recall the top-K relevant explanations for each question.
1 code implementation • 3 Oct 2023 • Junhao Lin, Qian Dai, Lei Zhu, Huazhu Fu, Qiong Wang, Weibin Li, Wenhao Rao, Xiaoyang Huang, Liansheng Wang
We also devise a localization-based contrastive loss to reduce the lesion location distance between neighboring video frames within the same video and enlarge the location distances between frames from different ultrasound videos.
2 code implementations • 31 May 2023 • Mingguo He, Zhewei Wei, Shikun Feng, Zhengjie Huang, Weibin Li, Yu Sun, dianhai yu
Furthermore, these methods cannot learn arbitrary valid heterogeneous graph filters within the spectral domain, which have limited expressiveness.
Ranked #5 on Node Property Prediction on ogbn-mag
1 code implementation • 21 Feb 2023 • Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, dianhai yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo
Then, we combine the group aggregation and the learnable encodings into a Transformer encoder to capture the semantic information.
no code implementations • 28 Jan 2023 • Anfeng Cheng, Yiding Liu, Weibin Li, Qian Dong, Shuaiqiang Wang, Zhengjie Huang, Shikun Feng, Zhicong Cheng, Dawei Yin
To assess webpage quality from complex DOM tree data, we propose a graph neural network (GNN) based method that extracts rich layout-aware information that implies webpage quality in an end-to-end manner.
1 code implementation • 2 Dec 2021 • Weibin Li, Mingkai He, Zhengjie Huang, Xianming Wang, Shikun Feng, Weiyue Su, Yu Sun
In recent years, owing to the outstanding performance in graph representation learning, graph neural network (GNN) techniques have gained considerable interests in many real-world scenarios, such as recommender systems and social networks.
1 code implementation • 28 Jun 2021 • Shanzhuo Zhang, Lihang Liu, Sheng Gao, Donglong He, Xiaomin Fang, Weibin Li, Zhengjie Huang, Weiyue Su, Wenjin Wang
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules.
no code implementations • 8 May 2021 • Weibin Li, Qiwei Zhong, Qingyang Zhao, Hongchun Zhang, Xiaonan Meng
In this paper, we propose a Multimodal and Contrastive learning network for Click Fraud detection (MCCF).
1 code implementation • NA 2021 • Weibin Li, Shanzhuo Zhang, Lihang Liu, Zhengjie Huang, Jieqiong Lei, Xiaomin Fang, Shikun Feng, Fan Wang
As graph neural networks have achieved great success in many domains, some studies apply graph neural networks to molecular property prediction and regard each molecule as a graph.
Ranked #6 on Graph Property Prediction on ogbg-molhiv
no code implementations • 3 Dec 2020 • Filippo Maria Gambetta, Chi Zhang, Markus Hennrich, Igor Lesanovsky, Weibin Li
Conical intersections between electronic potential energy surfaces are paradigmatic for the study of non-adiabatic processes in the excited states of large molecules.
Atomic Physics Quantum Physics