1 code implementation • 21 Dec 2023 • Chengen Lai, Shengli Song, Shiqi Meng, Jingyang Li, Sitong Yan, GuangNeng Hu
To address the above issues, we propose a novel self-supervised \textbf{M}ulti-level \textbf{C}ontrastive \textbf{L}earning based natural language \textbf{E}xplanation model (MCLE) for VQA with semantic-level, image-level, and instance-level factual and counterfactual samples.
1 code implementation • 16 Mar 2021 • Bairan Fu, Wenming Zhang, GuangNeng Hu, Xinyu Dai, ShuJian Huang, Jiajun Chen
Specifically, we first proposed a novel graph neural network to model the social relation and collaborative relation, and on top of high-order relations, a dual side deep context-aware modulation is introduced to capture the friends' information and item attraction.
no code implementations • EACL 2021 • GuangNeng Hu, Qiang Yang
To take advantage of the existing corpus, we propose a transfer learning model (dubbed as TrNews) for news recommendation to transfer the knowledge from a source corpus to a target corpus.
no code implementations • Findings of the Association for Computational Linguistics 2020 • GuangNeng Hu, Qiang Yang
Existing research focuses on the recommendation performance of the target domain while ignores the privacy leakage of the source domain.
no code implementations • 17 Apr 2018 • GuangNeng Hu, Yu Zhang, Qiang Yang
By modeling content information as local memories, LCMR attentively learns what to exploit with the guidance of user-item interaction.