1 citations · 6 across the 11 of their papers we have counts for
11 papers
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation
Hanwen Du, Huanhuan Yuan, Pengpeng Zhao +4
Sequential recommendation aims to capture users' dynamic interest and predicts the next item of users' preference. Most sequential recommendation methods use a deep neural network…
Sequential Recommendation with Probabilistic Logical Reasoning
Huanhuan Yuan, Pengpeng Zhao, Xuefeng Xian +3
Deep learning and symbolic learning are two frequently employed methods in Sequential Recommendation (SR). Recent neural-symbolic SR models demonstrate their potential to enable SR…
Long-Document Cross-Lingual Summarization
Shaohui Zheng, Zhixu Li, Jiaan Wang +4
Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language. CLS has attracted wide research attention due to its pra…
Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Yufeng Zhang, Weiqing Wang, Hongzhi Yin +3
Inductive link prediction (ILP) is to predict links for unseen entities in emerging knowledge graphs (KGs), considering the evolving nature of KGs. A more challenging scenario is t…
Contrastive Learning with Bidirectional Transformers for Sequential Recommendation
Hanwen Du, Hui Shi, Pengpeng Zhao +5
Contrastive learning with Transformer-based sequence encoder has gained predominance for sequential recommendation. It maximizes the agreements between paired sequence augmentation…
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
Kexin Wang, Zhixu Li, Jiaan Wang +4
Grounding dialogue system with external knowledge is a promising way to improve the quality of responses. Most existing works adopt knowledge graphs (KGs) as the external resources…
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Xuefeng Xian +5
Sequential Recommendation aims to predict the next item based on user behaviour. Recently, Self-Supervised Learning (SSL) has been proposed to improve recommendation performance. H…
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Jiaan Wang, Beiqi Zou, Zhixu Li +4
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context. The key challenges of the task lie in…
HFUL: A Hybrid Framework for User Account Linkage across Location-Aware Social Networks
Wei Chen, Weiqing Wang, Hongzhi Yin +2
Sources of complementary information are connected when we link user accounts belonging to the same user across different platforms or devices. The expanded information promotes th…
Knowledge Enhanced Sports Game Summarization
Jiaan Wang, Zhixu Li, Tingyi Zhang +5
Sports game summarization aims at generating sports news from live commentaries. However, existing datasets are all constructed through automated collection and cleaning processes,…
Quaternion-Based Graph Convolution Network for Recommendation
Yaxing Fang, Pengpeng Zhao, Guanfeng Liu +4
Graph Convolution Network (GCN) has been widely applied in recommender systems for its representation learning capability on user and item embeddings. However, GCN is vulnerable to…