| 2026 | WWW | Dynamic Routing-Based Adaptive Multi-LLM Collaboration: A Unified Recommendation Framework with Decision Knowledge Complementation. | Jiale Huang, Yingyuan Xiao, Likang Wu, Xu Cheng, Wenguang Zheng, Qingbo Hao, Ming He, Hongke Zhao |
| 2026 | WWW | Hierarchical Semantic RL: Tackling the Problem of Dynamic Action Space for RL-based Recommendations. | Minmao Wang, Xingchen Liu, Shijie Yi, Likang Wu, Hongke Zhao, Fei Pan, Qingpeng Cai, Peng Jiang |
| 2026 | WSDM | TemporalExpertNet: Cross-Temporal Knowledge Reuse for Promotion-Aware CVR Prediction. | Minmao Wang, Rui Zhang, Shijie Yi, Likang Wu, Hongke Zhao, Fei Pan, Qingpeng Cai, Peng Jiang |
| 2025 | AAAI | Multi-View Empowered Structural Graph Wordification for Language Models. | Zipeng Liu, Likang Wu, Ming He, Zhong Guan, Hongke Zhao, Nan Feng |
| 2025 | ICML | Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data. | Zhong Guan, Likang Wu, Hongke Zhao, Ming He, Jianping Fan |
| 2025 | IJCAI | TCDM: A Temporal Correlation-Empowered Diffusion Model for Time Series Forecasting. | Huibo Xu, Likang Wu, Xianquan Wang, Zhiding Liu, Qi Liu |
| 2025 | KDD | Mitigating Redundancy in Deep Recommender Systems: A Field Importance Distribution Perspective. | Xianquan Wang, Likang Wu, Zhi Li, Haitao Yuan, Shuanghong Shen, Huibo Xu, Yu Su, Chenyi Lei |
| 2025 | NAACL | Instruct-of-Reflection: Enhancing Large Language Models Iterative Reflection Capabilities via Dynamic-Meta Instruction. | Liping Liu, Chunhong Zhang, Likang Wu, Chuang Zhao, Zheng Hu, Ming He, Jianping Fan |
| 2025 | WSDM | Enhancing Code Search Intent with Programming Context Exploration. | Yanmin Dong, Zhenya Huang, Zheng Zhang, Guanhao Zhao, Likang Wu, Hongke Zhao, Binbin Jin, Qi Liu |
| 2024 | AAAI | A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction. | Wenshuo Chao, Zhaopeng Qiu, Likang Wu, Zhuoning Guo, Zhi Zheng, Hengshu Zhu, Hao Liu |
| 2024 | AAAI | Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations. | Likang Wu, Zhaopeng Qiu, Zhi Zheng, Hengshu Zhu, Enhong Chen |
| 2024 | CIKM | FZR: Enhancing Knowledge Transfer via Shared Factors Composition in Zero-Shot Relational Learning. | Zhijun Dong, Likang Wu, Kai Zhang, Ye Liu, Yanghai Zhang, Zhi Li, Hongke Zhao, Enhong Chen |
| 2024 | EMNLP | I-AM-G: Interest Augmented Multimodal Generator for Item Personalization. | Xianquan Wang, Likang Wu, Shukang Yin, Zhi Li, Yanjiang Chen, Hufeng Hufeng, Yu Su, Qi Liu |
| 2024 | IJCNN | Rethinking Offline Reinforcement Learning for Sequential Recommendation from A Pair-Wise Q-Learning Perspective. | Runqi Yang, Liu Yu, Zhi Li, Shaohui Li, Likang Wu |
| 2024 | WWW | Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation. | Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, Enhong Chen |
| 2024 | SIGIR | Cross-reconstructed Augmentation for Dual-target Cross-domain Recommendation. | Qingyang Mao, Qi Liu, Zhi Li, Likang Wu, Bing Lv, Zheng Zhang |
| 2023 | AAAI | Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense. | Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, Zaixi Zhang |
| 2023 | CIKM | Knowledge-Aware Cross-Semantic Alignment for Domain-Level Zero-Shot Recommendation. | Junji Jiang, Hongke Zhao, Ming He, Likang Wu, Kai Zhang, Jianping Fan |
| 2023 | CIKM | APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. | Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen |
| 2023 | DASFAA | GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation. | Yongqiang Han, Likang Wu, Hao Wang, Guifeng Wang, Mengdi Zhang, Zhi Li, Defu Lian, Enhong Chen |
| 2023 | IJCAI | KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification. | Likang Wu, Junji Jiang, Hongke Zhao, Hao Wang, Defu Lian, Mengdi Zhang, Enhong Chen |
| 2023 | KDD | Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation. | Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen |
| 2022 | SIGIR | Preference Enhanced Social Influence Modeling for Network-Aware Cascade Prediction. | Likang Wu, Hao Wang, Enhong Chen, Zhi Li, Hongke Zhao, Jianhui Ma |
| 2021 | DASFAA | Learning the Implicit Semantic Representation on Graph-Structured Data. | Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Jun Wang, Mengdi Zhang, Enhong Chen |
| 2021 | SIGIR | Enhanced Representation Learning for Examination Papers with Hierarchical Document Structure. | Yixiao Ma, Shiwei Tong, Ye Liu, Likang Wu, Qi Liu, Enhong Chen, Wei Tong, Zi Yan |
| 2020 | AAAI | Estimating Early Fundraising Performance of Innovations via Graph-Based Market Environment Model. | Likang Wu, Zhi Li, Hongke Zhao, Zhen Pan, Qi Liu, Enhong Chen |
| 2020 | IJCAI | Learning the Compositional Visual Coherence for Complementary Recommendations. | Zhi Li, Bo Wu, Qi Liu, Likang Wu, Hongke Zhao, Tao Mei |