Research

The long-term research goal is to build AI models for modern education, such as deep learning models, pre-trained models, and large models. We create new theories, algorithms, applications, and open-source libraries to achieve our goal. These days, we are specifically interested in Knowledge Representation and Reasoning, AI for Education and Recommendation, and Trustworthy AI, Security and Data Privacy.

Our research consists of the following topics with selected publications: View by year | Google Scholar

Awards

• Rethinking Variational Bayes in Community Detection from Graph Signal Perspective. Guangdong Computer Federation, Best Paper Award ‘25.
• On the Role of Logical Separability in Knowledge Compilation. Guangdong Computer Federation, Best Paper Award ‘24.
• Students’ Experience of Online Learning during the COVID-19 Pandemic: A Province-Wide Survey Study. British Journal of Educational Technology, Top Cited Article ‘21–22.
• Students’ Experience of Online Learning during the COVID-19 Pandemic: A Province-Wide Survey Study. British Journal of Educational Technology, Top Downloaded Article ‘21–22.
• Adaptive Convolutional Time Series Evaluation for Attack Behavior Postures. International Conference on Electrical, Electronics and Information Science (EEIS 2024), Best Paper Award.

Knowledge Representation, Embodied Intelligence‌ and Reasoning (Personal website: Google Scholar)

• [AAAI’26] Generating In-Distribution Counterfactual Explanation for Graph Neural Networks. Linmao Chen, Chaobo He, Junwei Cheng, Chunying Li, Quanlong Guan.
• [CVPR’26] Vocabulary Scaling Law: Tuning Open-Vocabulary Predictors for Their Openness. Ziliang Chen, Yulu Li, Liangda Fang, Jusheng Zhang, Yongsen Zheng, Quanlong Guan, Xipeng Chen.
• [ICML’26] Entangled No More: Multi-Domain Decoupling for Robust Dynamic Graph Neural Networks. Youda Mo, Chaobo He, Junwei Cheng, Peng Mei, Quanlong Guan.
• [EAAI’26] Zero-Shot Industrial Defect Detection in Flexible Manufacturing via General-Expert Prompt Fusion and Spatial Interaction. Yue Ai, Jiang Cheng, Jiahao Lai, Lingxi Peng, Quanlong Guan, Zhiwen Yu.
• [KBS’26] Manifold-Aware Triple Cooperative Multi-Population Differential Evolution with Reinforcement Learning for Irregular 3D UAV Path Planning. Yunhui Zhang, Guanglong Du, Hao Tang, Ziwei Wang, Xueqian Wang, Cuifeng Du, Quanlong Guan, Xiaojian Qiu.
• [Industrial Robot’26] A Framework for Vision-Based Robotic Grasping and Sorting in Cluttered Environments. Chuxin Chen, Jiaqi Wang, Jingwei Liu, Guanglong Du, Xiaojun Zhu, Quanlong Guan, Xiaojian Qiu.
• [Industrial Robot’26] A Non-Contact, Wide-Ranging Approach to Human–Robot Interaction Based on Broad Learning System. Jingwei Liu, Yufan Zhang, Bidan Li, Guanglong Du, Xiaojun Zhu, Quanlong Guan.
• [PR’25] GraphST: Class-Imbalanced Node Classification with Semantic Relation Transfer. Jialong Wang, Quanlong Guan, Lianbing Deng, Mengting Zhou, Zhiguo Gong.
• [IJCAI’25] Improvements to the Generate-and-Complete Approach to Conformant Planning. Liangda Fang, Min Zhan, Jin Tong, Xiujie Huang, Ziliang Chen, Quanlong Guan.
• [UAI’25] DyGMAE: A Novel Dynamic Graph Masked Autoencoder for Link Prediction. Weixiong Liu, Junwei Cheng, Zhongyu Pan, Chaobo He, Quanlong Guan.
• [CVPR’25] Reproducible Vision-Language Models Meet Concepts Out of Pre-Training. Ziliang Chen, Xin Huang, Xiaoxuan Fan, Keze Wang, Yuyu Zhou, Quanlong Guan, Liang Lin.
• [DASFAA’25] Boost Dynamic Community Detection via Exploiting Member Transition Information. Zhongyu Pan, Junwei Cheng, Weixiong Liu, Chaobo He, Quanlong Guan, Xuequan Lin.
• [AAAI’25] A Syntactic Approach to Computing Complete and Sound Abstraction in the Situation Calculus. Liangda Fang, Xiaoman Wang, Zhang Chen, Kailun Luo, Zhenhe Cui, Quanlong Guan.
• [TKDE’25] Rethinking Variational Bayes in Community Detection from Graph Signal Perspective. Junwei Cheng, Yong Tang, Chaobo He, Pengxing Feng, Kunlin Han, Quanlong Guan.
• [Neural Networks’25] Signed Graph Embedding via Multi-Order Neighborhood Feature Fusion and Contrastive Learning. Chaobo He, Hao Cheng, Jiaqi Yang, Yong Tang, Quanlong Guan.
• [AAMAS’25] Automatic Verification of Linear Integer Planning Programs via Forgetting in LIAUPF. Liangda Fang, Shikang Chen, Xiaoman Wang, Xiaoyou Lin, Chenyi Zhang, Qingliang Chen, Quanlong Guan, Kaile Su.
• [IJCAI’24] On the Logic of Theory Change Iteration of KM-Update, Revised. Liangda Fang, Tong Zhu, Quanlong Guan, Junming Qiu, Zhao-Rong Lai, Weiqi Luo, Hai Wan.
• [IJCAI’24] A Multi-Valued Decision Diagram-Based Approach to Constrained Optimal Path Problems over Directed Acyclic Graphs. Mingwei Zhang, Liangda Fang, Zhenhao Gu, Quanlong Guan, Yong Lai.
• [AAMAS’24] Generalized Strategy Synthesis of Infinite-State Impartial Combinatorial Games via Exact Binary Classification. Liangda Fang, Meihong Yang, Dingliang Cheng, Yunlai Hao, Quanlong Guan, Liping Xiong.
• [ICASSP’24] Deformation and Penetration Hybrid Detection-Net for Parcels Inspection in Industrial Supply Chain. Zhi Chen, Cuifeng Du, Xiujie Huang, Zelong Lin, Yuyu Zhou, Quanlong Guan, Zhefu Li, Shuanghuan Lv, Xiaofeng Wu, Xiaotian Zhuang.
• [AIJ’24] On the Role of Logical Separability in Knowledge Compilation. Junming Qiu, Wenqing Li, Liangda Fang, Quanlong Guan, Zhanhao Xiao, Zhao-Rong Lai, Qian Dong.
• [Information Sciences’23] Face2Nodes: Learning Facial Expression Representations with Relation-Aware Dynamic Graph Convolution Networks. Fan Jiang, Qionghao Huang, Xiaoyong Mei, Quanlong Guan, Yaxin Tu, Weiqi Luo, Changqin Huang.
• [ICCV’23] A Retrospect to Multi-Prompt Learning across Vision and Language. Ziliang Chen, Xin Huang, Quanlong Guan, Liang Lin, Weiqi Luo.
• [PR’22] Molecular Substructure Graph Attention Network for Molecular Property Identification in Drug Discovery. Xian-Bin Ye, Quanlong Guan, Weiqi Luo, Liangda Fang, Zhao-Rong Lai, Jun Wang.
• [AAAI’22] Knowledge Compilation Meets Logical Separability. Junming Qiu, Wenqing Li, Zhanhao Xiao, Quanlong Guan, Liangda Fang, Zhao-Rong Lai, Qian Dong.
• [TNNLS’22] Multitrend Conditional Value at Risk for Portfolio Optimization. Zhao-Rong Lai, Cheng Li, Xiaotian Wu, Quanlong Guan, Liangda Fang.
• [ICAPS’22] Generalized Linear Integer Numeric Planning. Xiaoyou Lin, Qingliang Chen, Liangda Fang, Quanlong Guan, Weiqi Luo, Kaile Su.
• [ICCAD’20] Dynamic Minimization of Bi-Kronecker Functional Decision Diagrams. Xuanxiang Huang, Haipeng Che, Liangda Fang, Qingliang Chen, Quanlong Guan, Yuhui Deng, Kaile Su.

AI for Education and Recommendation

• [KAIS’26] Enhancing Social Recommendation via Self-Supervised Social Relations Refinement. Chaobo He, Xinran Chen, Feiyu Peng, Peng Mei, Huijuan Hu, Quanlong Guan.
• [SIGIR’26] Mitigating Evidence Suppression: Bi-Level Active Evidence Injection for Educational Video Understanding. Cheng Liu, Yiping Wang, Quanlong Guan, Chaobo He, Xingyu Zhu, Liangda Fang.
• [AAAI’26] GraphRAG-Induced Dual Knowledge Structure Graphs for Personalized Learning Path Recommendation. Xinghe Cheng, Zihan Zhang, Jiapu Wang, Liangda Fang, Chaobo He, Quanlong Guan, Shirui Pan, Weiqi Luo.
• [CIKM’25] PERC: A Prior-Guided Framework for Classifying Long-Content Educational Resources with Imbalanced Category Distributions. Quanlong Guan, Xiuliang Duan, Zhi Chen, Xingyu Zhu, Jianbo Huang, Xinzhong Liu, Zonglin Liu, Liangda Fang.
• [SIGIR’25] NR4DER: Neural Re-Ranking for Diversified Exercise Recommendation. Xinghe Cheng, Xufang Zhou, Liangda Fang, Chaobo He, Yuyu Zhou, Weiqi Luo, Zhiguo Gong, Quanlong Guan.
• [Neural Networks’25] Explainable Exercise Recommendation with Knowledge Graph. Quanlong Guan, Xinghe Cheng, Fang Xiao, Zhuzhou Li, Chaobo He, Liangda Fang, Guanliang Chen, Zhiguo Gong, Weiqi Luo.
• [COLING’25] KVFKT: A New Horizon in Knowledge Tracing with Attention-Based Embedding and Forgetting Curve Integration. Quanlong Guan, Xiuliang Duan, Kaiquan Bian, Guanliang Chen, Jianbo Huang, Zhiguo Gong, Liangda Fang.
• [MM’24] Reason-and-Execute Prompting: Enhancing Multi-Modal Large Language Models for Solving Geometry Questions. Xiuliang Duan, Dating Tan, Liangda Fang, Yuyu Zhou, Chaobo He, Ziliang Chen, Lusheng Wu, Guanliang Chen, Zhiguo Gong, Weiqi Luo, Quanlong Guan.
• [AAAI’24] Unveiling the Tapestry of Automated Essay Scoring: A Comprehensive Investigation of Accuracy, Fairness, and Generalizability. Kaixun Yang, Mladen Raković, Yuyang Li, Quanlong Guan, Dragan Gašević, Guanliang Chen.
• [CIKM’23] KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation. Quanlong Guan, Fang Xiao, Xinghe Cheng, Liangda Fang, Ziliang Chen, Guanliang Chen, Weiqi Luo.
• [CogSci’23] An Interpretable Model with Forgetting Matrix for Deep Knowledge Tracing. Quanlong Guan, Kaiquan Bian, Liangda Fang, Sheng Li, Zhenyu He, Hua Zheng, Lusheng Wu, Weiqi Luo.
• [CIKM’22] Cognitive Diagnosis Focusing on Knowledge Concepts. Sheng Li, Quanlong Guan, Liangda Fang, Fang Xiao, Zhenyu He, Yizhou He, Weiqi Luo.

Trustworthy AI, Reliability, Security and Data Privacy

• [RESS’26] Reliability Analysis for Linear Multi-State (n, f, k) and ⟨n, f, k⟩ Systems. Shuaihao He, Chaonan Wang, Zhitao Wu, Quanlong Guan.
• [NeurIPS’25] FerretNet: Efficient Synthetic Image Detection via Local Pixel Dependencies. Shuqiao Liang, Jian Liu, Renzhang Chen, Quanlong Guan.
• [TITS’25] Task Offloading Based on the Fusion of Model- and Data-Driven Intelligence for Vehicular Edge Computing Networks. Xiujie Huang, Yuhao Chen, Zhiquan Liu, Shancheng Zhao, Zhetao Li, Renzhang Chen, Quanlong Guan.
• [TITS’25] An Efficient and Multi-Dimensional Privacy-Preserving Platoon Communication Scheme in Vehicular Networks. Nuo Xu, Zhiquan Liu, Xuming Han, Quanlong Guan, Heng Sun, Xiujie Huang, Jianfeng Ma.
• [ISSRE’24] Exact Computation of Network Reliability with Sentential Decision Diagrams. Delong Li, Jiayu Zeng, Liangda Fang, Chaonan Wang, Lin Cui, Quanlong Guan.
• [ICASSP’24] Transformer Model with Multi-Type Classification Decisions for Intrusion Attack Detection of Track Traffic and Vehicle. Quanlong Guan, Tian Zhang, Yu Qin, Yuyu Zhou, Yangguang Zhu, Yuansheng Zhong, Xiujie Huang, Zhifei Duan, Zhefu Li, Changjiang Liu, Xiaofeng Wu.
• [AAAI’24] Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach. Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan, Liang Lin.
• [Computer Networks’19] Extensive Evaluation on the Performance and Behaviour of TCP Congestion Control Protocols under Varied Network Scenarios. Jinting Lin, Lin Cui, Yuxiang Zhang, Fung Po Tso, Quanlong Guan.