21 citations · 48 across the 16 of their papers we have counts for
16 papers
Search-R2: Enhancing Search-Integrated Reasoning via Actor-Refiner Collaboration
Bowei He, Minda Hu, Zenan Xu +7
Search-integrated reasoning enables language agents to transcend static parametric knowledge by actively querying external sources. However, training these agents via reinforcement…
ConSurv: Multimodal Continual Learning for Survival Analysis
Dianzhi Yu, Conghao Xiong, Yankai Chen +6
Survival prediction of cancers is crucial for clinical practice, as it informs mortality risks and influences treatment plans. However, a static model trained on a single dataset f…
Learning Binarized Representations with Pseudo-positive Sample Enhancement for Efficient Graph Collaborative Filtering
Yankai Chen, Yue Que, Xinni Zhang +2
Learning vectorized embeddings is fundamental to many recommender systems for user-item matching. To enable efficient online inference, representation binarization, which embeds la…
Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
Dianzhi Yu, Xinni Zhang, Yankai Chen +4
Continual learning (CL) aims to empower machine learning models to learn continually from new data, while building upon previously acquired knowledge without forgetting. As models…
Towards Effective Top-N Hamming Search via Bipartite Graph Contrastive Hashing
Yankai Chen, Yixiang Fang, Yifei Zhang +3
Searching on bipartite graphs serves as a fundamental task for various real-world applications, such as recommendation systems, database retrieval, and document querying. Conventio…
Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
Yankai Chen, Yixiang Fang, Qiongyan Wang +2
Node importance estimation problem has been studied conventionally with homogeneous network topology analysis. To deal with network heterogeneity, a few recent methods employ graph…
HiHPQ: Hierarchical Hyperbolic Product Quantization for Unsupervised Image Retrieval
Zexuan Qiu, Jiahong Liu, Yankai Chen +1
Existing unsupervised deep product quantization methods primarily aim for the increased similarity between different views of the identical image, whereas the delicate multi-level…
Hyperbolic Representation Learning: Revisiting and Advancing
Menglin Yang, Min Zhou, Rex Ying +2
The non-Euclidean geometry of hyperbolic spaces has recently garnered considerable attention in the realm of representation learning. Current endeavors in hyperbolic representation…
WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering
Yankai Chen, Yifei Zhang, Menglin Yang +3
Maximizing the user-item engagement based on vectorized embeddings is a standard procedure of recent recommender models. Despite the superior performance for item recommendations,…
Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space
Yankai Chen, Yixiang Fang, Yifei Zhang +1
Searching on bipartite graphs is basal and versatile to many real-world Web applications, e.g., online recommendation, database retrieval, and query-document searching. Given a que…
Knowledge-aware Neural Networks with Personalized Feature Referencing for Cold-start Recommendation
Xinni Zhang, Yankai Chen, Cuiyun Gao +3
Incorporating knowledge graphs (KGs) as side information in recommendation has recently attracted considerable attention. Despite the success in general recommendation scenarios, p…
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation
Yankai Chen, Huifeng Guo, Yingxue Zhang +4
Learning vectorized embeddings is at the core of various recommender systems for user-item matching. To perform efficient online inference, representation quantization, aiming to e…
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation
Yankai Chen, Yifei Zhang, Yingxue Zhang +5
Due to the promising advantages in space compression and inference acceleration, quantized representation learning for recommender systems has become an emerging research direction…
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation
Yankai Chen, Yaming Yang, Yujing Wang +3
To alleviate data sparsity and cold-start problems of traditional recommender systems (RSs), incorporating knowledge graphs (KGs) to supplement auxiliary information has attracted…
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
Yankai Chen, Menglin Yang, Yingxue Zhang +4
Aiming to alleviate data sparsity and cold-start problems of traditional recommender systems, incorporating knowledge graphs (KGs) to supplement auxiliary information has recently…
A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
Yankai Chen, Yaozu Wu, Shicheng Ma +1
With the rapid development of biomedical software and hardware, a large amount of relational data interlinking genes, proteins, chemical components, drugs, diseases, and symptoms h…