2024:

• Shaowei Wang, Lingling Zhang*, Wenjun Wu, Tao Qin*, Xinyu Zhang, Jun Liu. Alignment-guided Self-supervised Learning for Diagram Question Answering. IEEE Transactions on Multimedia (TMM) 2024.
• Bo Li, Lingling Zhang*, Jun Liu, Hong Peng. Multi-focus image fusion with parameter adaptive dual channel dynamic threshold neural P systems. Neural Networks, 2024.
• 李逸飞、张玲玲*、董宇轩、王佳欣、仲宇杰、魏笔凡，基于大语言模型增强表征对齐的小样本持续关系抽取方法，计算机科学与探索，2024.
• Lingling Zhang, Yifei Li,* Qianying Wang, Yun Wang, Hang Yan, Jiaxin Wang, and Jun Liu. FPrompt-PLM: Flexible-Prompt on Pretrained Language Model for Continual Few-Shot Relation Extraction. IEEE TKDE, 2024.
• Jiaxin Wang, Lingling Zhang*, Wee Sun Lee, Yujie Zhong, Liwei Kang, Jun Liu. When Phrases Meet Probabilities: Enabling Open Relation Extraction with Cooperating Large Language Models. ACL 2024.
• Shaowei Wang, Lingling Zhang*, Tao Qin*, Jun Liu, Yifei Li, Qianying Wang, Qinghua Zheng, Multi-View Cognition with Path Search for One-Shot Part Labeling, Computer Vision and Image Understanding (CVIU), 2024
• Xinyu Zhang, Lingling Zhang*, Xin Hu, Jun Liu, Shaowei Wang and Qianying Wang. Alignment Relation is What You Need for Diagram Parsing. IEEE  TIP, 2024, Accepted.
• Wenjun Wu, Lingling Zhang*, Jun Liu, Xi Tang, Yaxian Wang, Shaowei Wang, QianYing Wang.  E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator. CVPR 2024.
• Shaowei Wang, Lingling Zhang*, Longji Zhu, Tao Qin, Kim-Hui Yap, Xinyu Zhang, Jun Liu. CoG-DQA: Chain-of-Guiding Learning with Large Language Models for Diagram Question Answering. CVPR 2024.
• Yudai Pan, Jun Liu, Tianzhe Zhao, Lingling Zhang, QianyingWang. Context-Aware Commonsense Knowledge Graph Reasoning with Path-Guided Explanations, IEEE TKDE, 2024, Accepted.
• Yudai Pan, Jun Liu, Tianzhe Zhao, Lingling Zhang, Yun Lin, Jinsong Dong. A Symbolic Rule Integration Framework with Logic Transformer for Inductive Relation Prediction. WWW 2024.

2023:

• Fangzhi Xu, Jun Liu, Qika Lin, Tianzhe Zhao, Jian Zhang, Lingling Zhang, Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text, IEEE TNNLS, 2023, Accepted.
• 潘雨黛、张玲玲、蔡忠闵*、赵天哲、魏笔凡、刘均，基于大规模语言模型的知识图谱可微规则抽取，计算机科学与探索，2023.
• 郑庆华、张玲玲、龚铁梁、刘欢. 大数据知识工程, 科学出版社, 2023.
• Yaxian Wang, Bifan Wei, Jun Liu, Lingling Zhang, Jiaxin Wang, Qianying Wang, DisAVR: Disentangled Adaptive Visual Reasoning Network for Diagram Question Answering, IEEE TIP, 2023, Accepted.
• Yudai Pan, Jun Liu*, Lingling Zhang, Yi Huang, Incorporating logic rules with textual representations for interpretable knowledge graph reasoning, Knowledge-Based Systems，2023.
• Xin Hu, Lingling Zhang*, Jun Liu, Xinyu Zhang, Wenjun Wu, Qianying Wang. Diagram Visual Grounding: Learning to See with Gestalt-Perceptual Attention, IJCAI, 2023.
• Fangzhi Xu, Qika Lin, Jun Liu, Lingling Zhang, Tianzhe Zhao, Qi Chai, Yudai Pan, Yi Huang, Qianying Wang. MoCA: Incorporating Domain Pretraining and Cross Attention for Textbook Question Answering, Pattern Recognition, 2023(140): 109588.
• Lingling Zhang, Xinyu Zhang, Qianying Wang, Wenjun Wu, Xiaojun Chang, Jun Liu, RPMG-FSS: Robust Prior Mask Guided Few-Shot Semantic Segmentation, IEEE TCSVT, 2023.
• Yaxian Wang,  Jun Liu, Ma jie,  Hongwei Zeng, Lingling Zhang, Junjun Li, Dynamic Dual Graph Networks for Textbook Question Answering, Pattern Recognition, 2023.
• 郑庆华, 刘欢, 龚铁梁, 张玲玲, 刘均. 大数据知识工程发展现状与未来展望, 中国工程科学, 2023, 已录用.
• Xin Hu, Lingling Zhang*, Jun Liu, Jinfu Fan,  Yang You, Yaqiang Wu. GPTR: Gestalt-Perception Transformer for Diagram Object Detection. AAAI 2023.

2022:

• Yaxian Wang, Bifan Wei, Jun Liu, Qika Lin, Lingling Zhang, Yaqiang  Wu, Spatial-Semantic Collaborative Graph Network for Textbook Question Answering, IEEE TCSVT, 2022, Accepted.
• Jiaxin Wang, Lingling Zhang*, Jun Liu, Kunming Ma, Wenjun Wu, Xiang Zhao, Yaqiang Wu, Yi Huang. TGIN: Translation-Based Graph Inference Network for Few-Shot Relational Triplet Extraction. IEEE Transactions on Neural Networks and Learning Systems, 2022, Accepted.
• Yudai Pan, Jun Liu, Lingling Zhang, Tianzhe Zhao, Qika Lin, Xin Hu and Qianying Wang. Inductive Relation Prediction with Logical Reasoning Using Contrastive Representations. EMNLP 2022.
• Jiaxin Wang, Lingling Zhang*, Jun Liu, Liang Xi, Yujie Zhong and Yaqiang Wu. MatchPrompt: Prompt-based Open Relation Extraction with Semantic Consistency Guided Clustering. EMNLP 2022.
• Lingling Zhang, Xiaojun Chang, Jun Liu, Minnan Luo, Zhihui Li, Lina Yao, and Alex Hauptmann, TN-ZSTAD: Transferable Network for Zero-Shot Temporal Activity Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, Accepted.
• Lingling Zhang, Shaowei Wang, Jun Liu*, Xiaojun Chang, Qika Lin, Yaqiang Wu, and Qinghua Zheng. MuL-GRN: Multi-Level Graph Relation Network for Few-Shot Node Classification，IEEE Transactions on Knowledge and Data Engineering, 2022, Accepted.
• Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan and Lingling Zhang. Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning, SIGIR 2022.
• Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang and Tianzhe Zhao. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction, SIGIR 2022.
• Shaowei Wang, Linging Zhang*, Xuan Luo, Yi Yang, Xin Hu, Tao Qin*, Jun Liu, Computer Science Diagram Understanding with Topology Parsing, ACM Transactions on Knowledge Discovery from Data (TKDD), 2022.

2021:

• Qika Lin; Jun Liu, Lingling Zhang*, Yudai Pan, Xin Hu, Fangzhi Xu, Hongwei Zeng, Contrastive Graph Representations for Logical Formulas Embedding, IEEE Transactions on Knowledge and Data Engineering, 2021, Accepted.
• 张玲玲*,、陈一苇、吴文俊、魏笔凡、罗炫、常晓军、刘均，基于对比约束的可解释小样本学习，计算机研究与发展，2021（已录用）.
• Shaowei Wang, Lingling Zhang*, Yi Yang, Xin Hu, Tao Qin, Bifan Wei, Jun Liu, CSDQA: Diagram Question Answering in Computer Science, China Conference on Knowledge Graph and Semantic Computing. Springer, Singapore, 2021: 274-280. （最佳论文资源奖）
• Wenjun Wu, Lingling Zhang*, Yiwei Chen, Xuan Luo, Bifan Wei, Jun Liu, Fuzzy c-Means Clustering with Discriminative Projection, ICBK 2021
• Xin Hu, Lingling Zhang*, Jun Liu, Qinghua Zheng, Jianlong Zhou, Fs-DSM: Few-Shot Diagram-Sentence Matching via Cross-Modal Attention Graph Model, IEEE Transactions on Image Processing, 2021, Accepted.
• 蔺奇卡、张玲玲*、刘均、赵天哲，基于问句感知图卷积的教育知识库问答方法，计算机科学与探索，2021.
• 郑庆华、刘均、魏笔凡、张玲玲. 知识森林：理论、方法与实践, 科学出版社, 2021.
• Jun Liu, Lingling Zhang, Bifan Wei, Qinghua Zheng. Virtual Teaching Assistants: Technologies, Applications and Challenges. In: Fang Chen, Jianlong Zhou (Eds.), Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership, Springer, 2021.
• Qika Lin, Jun Liu, Yudai Pan, Lingling Zhang, Xin Hu, Jie Ma. Rule-Enhanced Iterative Complementation for Knowledge Graph Reasoning, Information Sciences, 2021, Accepted.
• Lingling Zhang, Shaowei Wang, Xiaojun Chang, Jun Liu, Zongyuan Ge, and Qinghua Zheng. Auto-FSL: Searching the Attribute Consistent Network for Few-Shot Learning, IEEE Transactions on Circuits and Systems for Video Technology, 2021, Accepted.
• Jinzhi Liao, Xiang Zhao, Xibyi Li, Lingling Zhang, Jiuyang Tang, Learning Discriminative Neural Representations for Event Detection, SIGIR, 2021.

2020年之前:

• Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng,  Graph Few-shot Learning with Attribute Matching, CIKM, 2020.
• Lingling Zhang, Xiaojun Chang, Jun Liu, Sen Wang, Zongyuan Ge, Minnan Luo, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, CVPR，2020.
• Xin Hu, Jun Liu, Jie Ma, Yudai Pan, Lingling Zhang, Fine-grained 3D-Attention Prototypes for FewShot Learning, Neural Computation, 2020.
• Lingling Zhang, Xiaojun Chang, Jiu Liu, Minnan Luo, and Alexander G. Hauptmann, Few-Shot Activity Recognition with Cross-Modal Memory Network, Pattern Recognition, 2020. (CCF B)
• Lingling Zhang, Minnan Luo, Zhihui Li, Feiping Nie, Huangxiang Zhang, Jun Liu, Qinghua Zheng. Large Scale Robust Semi-supervised Classification, IEEE Transactions on Cybernetics, 2018, 49(3): 907-917. (CCF B)
• Lingling Zhang, Minnan Luo, Jun Liu, Xiaojun Chang, Yi Yang, and Alexander G. Hauptmann. Deep Top-k Ranking for Image-Sentence Matching, IEEE Transactions on Multimedia, 2019. (CCF B)
• Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, and Alexander G. Hauptmann. Scheduled Sampling for One-Shot Learning via Matching Network, Pattern Recognition, 2019. (CCF B)
• Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng. Deep Semi-supervised Zero-shot Learning with Maximum Mean Discrepancy. Neural Computation, 2018, 30(5), 1426-1447. (CCF B)  
• Lingling Zhang, Minnan Luo, Jun Liu, Zhihui Li, Qinghua Zheng. Diverse fuzzy c-means for image clustering, Pattern Recognition Letter, 2018.
• Minnan Luo, Lingling Zhang, Feiping Nie, Xiaojun Chang, Buyue Qian, Qinghua Zheng. Adaptive Semi-supervised Learning with Discriminative Least Squares Regression, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017. (CCF A类会议)
• Minnan Luo, Lingling Zhang, Jun Liu and Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, Neurocomputing, 2017, 261, 164-170. 
• Lingyun Song, Minnan Luo, Jun Liu, Lingling Zhang, Haifei Li, Qinghua Zheng, Sparse Multi-Modal Topical Coding for Image Annotation, Neurocomputing, 2016, 214, 162-174.