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2020 – today
- 2024
[j2]Shiyao Cui
, Jiangxia Cao, Xin Cong, Jiawei Sheng, Quangang Li, Tingwen Liu, Jinqiao Shi:
Enhancing Multimodal Entity and Relation Extraction With Variational Information Bottleneck. IEEE ACM Trans. Audio Speech Lang. Process. 32: 1274-1285 (2024)- [c18]Wentao Xu, Qianqian Xie, Shuo Yang, Jiangxia Cao, Shuchao Pang:
Enhancing Content-based Recommendation via Large Language Model. CIKM 2024: 4153-4157 - [c17]Gaode Chen, Ruina Sun, Yuezihan Jiang, Jiangxia Cao, Qi Zhang, Jingjian Lin, Han Li, Kun Gai, Xinghua Zhang:
A Multi-modal Modeling Framework for Cold-start Short-video Recommendation. RecSys 2024: 391-400 - [c16]Xiaodong Li, Jiawei Sheng, Jiangxia Cao, Wenyuan Zhang, Quangang Li, Tingwen Liu:
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process. WSDM 2024: 378-386 - [i12]Wentao Xu, Qianqian Xie, Shuo Yang, Jiangxia Cao, Shuchao Pang:
Enhancing Content-based Recommendation via Large Language Model. CoRR abs/2404.00236 (2024) - [i11]Xu Wang, Jiangxia Cao, Zhiyi Fu, Kun Gai, Guorui Zhou:
HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou. CoRR abs/2408.05430 (2024) - [i10]Jiangxia Cao, Shen Wang, Yue Li, Shenghui Wang, Jian Tang, Shiyao Wang, Shuang Yang, Zhaojie Liu, Guorui Zhou:
Moment&Cross: Next-Generation Real-Time Cross-Domain CTR Prediction for Live-Streaming Recommendation at Kuaishou. CoRR abs/2408.05709 (2024) - [i9]Jiangxia Cao, Shen Wang, Gaode Chen, Rui Huang, Shuang Yang, Zhaojie Liu, Guorui Zhou:
A Unified Framework for Cross-Domain Recommendation. CoRR abs/2409.04540 (2024) - [i8]Haipeng Li, Jiangxia Cao, Yiwen Gao, Yunhuai Liu, Shuchao Pang:
Cross-Domain Sequential Recommendation via Neural Process. CoRR abs/2410.13588 (2024) - 2023
- [j1]Xiaobo Guo, Shaoshuai Li, Naicheng Guo, Jiangxia Cao, Xiaolei Liu, Qiongxu Ma, Runsheng Gan, Yunan Zhao:
Disentangled Representations Learning for Multi-target Cross-domain Recommendation. ACM Trans. Inf. Syst. 41(4): 85:1-85:27 (2023) - [c15]Gehang Zhang, Bowen Yu, Jiangxia Cao, Xinghua Zhang, Jiawei Sheng, Chuan Zhou, Tingwen Liu:
ID-MixGCL: Identity Mixup for Graph Contrastive Learning. IEEE Big Data 2023: 473-482 - [c14]Jiawei Sheng, Xin Cong, Jiangxia Cao, Shu Guo, Chen Li, Lihong Wang, Tingwen Liu, Hongbo Xu:
Uncertain Relational Hypergraph Attention Networks for Document-Level Event Factuality Identification. ECAI 2023: 2129-2137 - [c13]Xinghua Zhang, Bowen Yu, Jiangxia Cao, Quangang Li, Xuebin Wang, Tingwen Liu, Hongbo Xu:
Representation and Labeling Gap Bridging for Cross-lingual Named Entity Recognition. SIGIR 2023: 1230-1240 - [c12]Jiangxia Cao, Shaoshuai Li, Bowen Yu, Xiaobo Guo, Tingwen Liu, Bin Wang:
Towards Universal Cross-Domain Recommendation. WSDM 2023: 78-86 - [i7]Shiyao Cui, Jiangxia Cao, Xin Cong, Jiawei Sheng, Quangang Li, Tingwen Liu, Jinqiao Shi:
Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck. CoRR abs/2304.02328 (2023) - [i6]Jiangxia Cao, Xin Cong, Jiawei Sheng, Tingwen Liu, Bin Wang:
Contrastive Cross-Domain Sequential Recommendation. CoRR abs/2304.03891 (2023) - [i5]Gehang Zhang, Bowen Yu, Jiangxia Cao, Xinghua Zhang, Tingwen Liu, Chuan Zhou:
ID-MixGCL: Identity Mixup for Graph Contrastive Learning. CoRR abs/2304.10045 (2023) - 2022
- [c11]Yanzeng Li, Jiangxia Cao, Xin Cong, Zhenyu Zhang, Bowen Yu, Hongsong Zhu, Tingwen Liu:
Enhancing Chinese Pre-trained Language Model via Heterogeneous Linguistics Graph. ACL (1) 2022: 1986-1996 - [c10]Jiangxia Cao, Xin Cong, Jiawei Sheng, Tingwen Liu, Bin Wang:
Contrastive Cross-Domain Sequential Recommendation. CIKM 2022: 138-147 - [c9]Jiangxia Cao, Jiawei Sheng, Xin Cong, Tingwen Liu, Bin Wang:
Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck. ICDE 2022: 2209-2223 - [c8]Jiangxia Cao, Xixun Lin, Xin Cong, Jing Ya, Tingwen Liu, Bin Wang:
DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation. SIGIR 2022: 267-277 - [c7]Jiawei Sheng, Rui Sun, Shu Guo, Shiyao Cui, Jiangxia Cao, Lihong Wang, Tingwen Liu, Hongbo Xu:
CorED: Incorporating Type-level and Instance-level Correlations for Fine-grained Event Detection. SIGIR 2022: 1122-1132 - [c6]Jiangxia Cao, Xin Cong, Tingwen Liu, Bin Wang:
Item Similarity Mining for Multi-Market Recommendation. SIGIR 2022: 2249-2254 - [i4]Jiangxia Cao, Jiawei Sheng, Xin Cong, Tingwen Liu, Bin Wang:
Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck. CoRR abs/2203.16863 (2022) - 2021
- [c5]Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, Bin Wang:
Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. ICDM 2021: 360-369 - [c4]Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo, Hengzhu Tang, Tingwen Liu, Bin Wang:
Deep Structural Point Process for Learning Temporal Interaction Networks. ECML/PKDD (1) 2021: 305-320 - [c3]Jing Ya, Tingwen Liu, Jiangxia Cao, Li Guo:
Heterogeneous Graph Neural Networks for Query-focused Summarization. SDM 2021: 720-728 - [c2]Jiangxia Cao, Xixun Lin, Shu Guo, Luchen Liu, Tingwen Liu, Bin Wang:
Bipartite Graph Embedding via Mutual Information Maximization. WSDM 2021: 635-643 - [i3]Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo, Hengzhu Tang, Tingwen Liu, Bin Wang:
Deep Structural Point Process for Learning Temporal Interaction Networks. CoRR abs/2107.03573 (2021) - 2020
- [c1]Hengzhu Tang, Yanan Cao, Zhenyu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, Pengfei Yin:
HIN: Hierarchical Inference Network for Document-Level Relation Extraction. PAKDD (1) 2020: 197-209 - [i2]Hengzhu Tang, Yanan Cao, Zhenyu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, Pengfei Yin:
HIN: Hierarchical Inference Network for Document-Level Relation Extraction. CoRR abs/2003.12754 (2020) - [i1]Jiangxia Cao, Xixun Lin, Shu Guo, Luchen Liu, Tingwen Liu, Bin Wang:
Bipartite Graph Embedding via Mutual Information Maximization. CoRR abs/2012.05442 (2020)
Coauthor Index
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