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Jiaqi Zhu 0001
Person information
- affiliation: Chinese Academy of Sciences, Institute of Software, Beijing, China
- affiliation: University of California, Los Angeles, CA, USA
- affiliation: United Nations University Institute in Macau, International Institute of Software Technology, Macao
- affiliation (PhD 2009): Peking University, School of Information Science and Technology, Beijing, China
Other persons with the same name
- Jiaqi Zhu — disambiguation page
- Jiaqi Zhu 0002
— Beijing Institute of Technology, National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing, China
- Jiaqi Zhu 0003
— Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, Hong Kong (and 1 more)
- Jiaqi Zhu 0004 — Tencent, Hunyuan Team
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2020 – today
- 2025
- [c13]Jiafan Li, Jiaqi Zhu, Liang Chang, Yilin Li, Miaomiao Li, Yang Wang, Yi Yang, Hongan Wang:
Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks. IJCAI 2025: 3036-3044 - [i2]Jiafan Li, Jiaqi Zhu, Liang Chang, Yilin Li, Miaomiao Li, Yang Wang, Hongan Wang:
Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks. CoRR abs/2505.07895 (2025) - 2024
- [j2]Xiaojun Pu
, Jiaqi Zhu, Yunkun Wu, Chang Leng, Zitong Bo, Hongan Wang:
Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting. CAAI Trans. Intell. Technol. 9(3): 769-786 (2024) - [c12]Yun Li
, Yi Yang
, Jiaqi Zhu
, Hui Chen
, Hongan Wang
:
LLM-Empowered Few-Shot Node Classification on Incomplete Graphs with Real Node Degrees. CIKM 2024: 1306-1315 - [c11]Miaomiao Li
, Jiaqi Zhu
, Yang Wang
, Yi Yang
, Yilin Li
, Hongan Wang
:
RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules. WWW 2024: 4272-4282 - [i1]Miaomiao Li, Jiaqi Zhu, Yang Wang, Yi Yang, Yilin Li, Hongan Wang:
RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules. CoRR abs/2403.02932 (2024) - 2023
- [c10]Yilin Li
, Jiaqi Zhu
, Congcong Zhang
, Yi Yang
, Jiawen Zhang
, Ying Qiao
, Hongan Wang
:
THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks. CIKM 2023: 1368-1378 - [c9]Miaomiao Li
, Jiaqi Zhu
, Xin Yang
, Yi Yang
, Qiang Gao
, Hongan Wang
:
CL-WSTC: Continual Learning for Weakly Supervised Text Classification on the Internet. WWW 2023: 1489-1499 - 2021
- [c8]Yi Yang
, Hongan Wang, Jiaqi Zhu
, Wandong Shi, Wenli Guo, Jiawen Zhang
:
Effective Seed-Guided Topic Labeling for Dataless Hierarchical Short Text Classification. ICWE 2021: 271-285 - [c7]Jiawen Zhang
, Jiaqi Zhu, Yi Yang
, Wandong Shi, Congcong Zhang, Hongan Wang:
Knowledge-Enhanced Domain Adaptation in Few-Shot Relation Classification. KDD 2021: 2183-2191 - 2020
- [c6]Yi Yang
, Hongan Wang, Jiaqi Zhu, Yunkun Wu, Kailong Jiang, Wenli Guo, Wandong Shi:
Dataless Short Text Classification Based on Biterm Topic Model and Word Embeddings. IJCAI 2020: 3969-3975 - [c5]Jiawen Zhang
, Yuanyuan Zhao, Jiaqi Zhu, Jinba Xiao:
Distant Supervision for Polyphone Disambiguation in Mandarin Chinese. INTERSPEECH 2020: 1753-1757
2010 – 2019
- 2016
- [j1]Jiaqi Zhu, Kaijun Wang, Yunkun Wu, Zhongyi Hu, Hongan Wang:
Mining User-Aware Rare Sequential Topic Patterns in Document Streams. IEEE Trans. Knowl. Data Eng. 28(7): 1790-1804 (2016) - 2014
- [c4]Zhongyi Hu, Hongan Wang, Jiaqi Zhu:
The discovery of user related rare sequential patterns of topics in the internet document stream. SAC 2014: 137-138 - [c3]Zhongyi Hu, Hongan Wang, Jiaqi Zhu, Maozhen Li, Ying Qiao, Changzhi Deng:
Discovery of Rare Sequential Topic Patterns in Document Stream. SDM 2014: 533-541 - 2013
- [c2]Quan Zu, Miaomiao Zhang, Jiaqi Zhu, Naijun Zhan:
Bounded model-checking of discrete duration calculus. HSCC 2013: 213-222 - 2012
- [c1]Ruzhen Dong, Johannes Faber, Zhiming Liu, Jirí Srba
, Naijun Zhan, Jiaqi Zhu:
Unblockable compositions of software components. CBSE 2012: 103-108
Coauthor Index

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last updated on 2025-09-27 20:11 CEST by the dblp team
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