| 2026 | PAKDD | Learning Multi-aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation. | Qijiong Liu, Jieming Zhu, Zhaocheng Du, Lu Fan, Zhou Zhao, Xiao-Ming Wu |
| 2026 | SIGIR | Full Retraining, Incremental Fine-tuning, and Hybrid Serving: Model Updating and Serving for Industrial Generative Recommender Systems. | Lu Fan, Qijiong Liu, Zhongzhou Liu, Guoyuan An, Wei Guo, Yong Liu, Xiao-Ming Wu |
| 2026 | WSDM | Accelerating Generative Recommendation via Simple Categorical User Sequence Compression. | Qijiong Liu, Lu Fan, Zhongzhou Liu, Xiaoyu Dong, Yuankai Luo, Guoyuan An, Nuo Chen, Wei Guo, Yong Liu, Xiao-Ming Wu |
| 2025 | ACL | NetSafe: Exploring the Topological Safety of Multi-agent System. | Miao Yu, Shilong Wang, Guibin Zhang, Junyuan Mao, Chenlong Yin, Qijiong Liu, Kun Wang, Qingsong Wen, Yang Wang |
| 2025 | EMNLP | ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment. | Zhipeng Bian, Jieming Zhu, Qijiong Liu, Wang Lin, Guohao Cai, Zhaocheng Du, Jiacheng Sun, Zhou Zhao, Zhenhua Dong |
| 2025 | EMNLP | RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation. | Sashuai Zhou, Weinan Gan, Qijiong Liu, Ke Lei, Jieming Zhu, Hai Huang, Yan Xia, Ruiming Tang, Zhenhua Dong, Zhou Zhao |
| 2025 | ICDE | Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation (Extended Abstract). | Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang |
| 2025 | ICLR | Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning. | Yuankai Luo, Hongkang Li, Qijiong Liu, Lei Shi, Xiao-Ming Wu |
| 2025 | WWW | Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support. | Qijiong Liu, Lu Fan, Xiao-Ming Wu |
| 2025 | WWW | Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation. | Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang |
| 2024 | ACL | EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs. | Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu |
| 2024 | ECIR | Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision. | Hengchang Hu, Qijiong Liu, Chuang Li, Min-Yen Kan |
| 2024 | KDD | Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. | Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong |
| 2024 | RecSys | CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation. | Jieming Zhu, Mengqun Jin, Qijiong Liu, Zexuan Qiu, Zhenhua Dong, Xiu Li |
| 2024 | WWW | Discrete Semantic Tokenization for Deep CTR Prediction. | Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu |
| 2024 | WWW | Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. | Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu |
| 2024 | WWW | Benchmarking News Recommendation in the Era of Green AI. | Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu |
| 2024 | WSDM | ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models. | Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu |
| 2023 | AAAI | Continual Graph Convolutional Network for Text Classification. | Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding |
| 2023 | WWW | FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. | Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu |
| 2022 | COLING | Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. | Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiaoming Wu |
| 2019 | IJCAI | Weak Supervision Enhanced Generative Network for Question Generation. | Yutong Wang, Jiyuan Zheng, Qijiong Liu, Zhou Zhao, Jun Xiao, Yueting Zhuang |