2025

•  

• Herun Wan, Jiaying Wu, Minnan Luo*, Zhi Zeng, Zhixiong Su，Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection, NeurIPS 2025, Accepted.
• Zihan Ma, Taolin Zhang, Maosong Cao, Junnan Liu, Wenwei Zhang, Minnan Luo*, Songyang Zhang, Kai Chen, Rethinking Evaluation for LLM Code Generation: From Generation to Testing, NeurIPS 2025, Accepted.

• Herun Wan, Minnan Luo*, Zihan Ma, Guang Dai, Xiang Zhao，How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis, EMNLP 2025, Accepted.

• Yilin Wang, Heng Wang, Yuyang Bai, Minnan Luo*, Continuously Steering LLMs Sensitivity to Contextual Knowledge with Proxy Models, EMNLP 2025, Accepted.

• Zhi Zeng, Jiaying Wu, Minnan Luo*, Xiangzheng Kong, Zihan Ma, Guang Dai, Qinghua Zheng，Understand, Refine and Summarize: Multi-Granularity Knowledge Progressive Enhancement Learning for Fake News Video Detection, ACMM 2025, Accepted.

• Herun Wan, Minnan Luo*, Zhixiong Su, Guang Dai, Xiang Zhao, On the Risk of Evidence Pollution for Malicious Social Text Detection in the Era of LLMs, ACL 2025, Oral, Accepted.

• Zhi Zeng, Jiaying Wu, Minnan Luo*, Herun Wan, Xiangzheng Kong, Zihan Ma, Guang Dai, QinghuaZheng, IMOL:Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection, ACL 2025, Oral, Accepted.

• Zhixiong Su, Yichen Wang, Herun Wan, Zhaohan Zhang, Minnan Luo*, HACo-Det: A Study Towards Fine-Grained Machine-Generated Text Detection under Human-AI Coauthoring, ACL 2025, Accepted.

• Chenyou Jia, Minnan Luo*, Zhuohang Dang, Qiushi Sun, Fangzhi Xu, Junlin Hu, Tianbao Xie, Zhiyong Wu, AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant, ACL Findings 2025, Accepted.

• Zhuohang Dang, Minnan Luo*, Jihong Wang, Chengyou Jia, Haochen Han, Herun Wan, Guang Dai, Xiaojun Chang, and Jingdong Wang, Disentangled Noisy Correspondence Learning, IEEE TIP, Accepted.

• Haochen Han, Minnan Luo, Huan Liu, Fang Nan, Jun Liu. A Unified Optimal Transport Framework for Cross-Modal Retrieval with Noisy Labels. IEEE TNNLS, Accepted.

• Zihan Ma, Minnan Luo*, Yiran Hao, Zhi Zeng, Xiangzheng Kong, Jiahao Wang, Bridging Interests and Truth: Towards Mitigating Fake News with Personalized and Truthful Recommendations, SIGIR 2025.

• Xiaofan Zheng, Zinan Zeng, Heng Wang, Yuyang Bai, Yuhan Liu, Minnan Luo*, From Predictions to Analyses: Rationale-Augmented Fake News Detection with Large Vision-Language Models, Proceedings of the ACM on Web Conference, 2025.

• Hao Guo, Zihan Ma, Zhi Zeng, Minnan Luo*, Weixin Zeng, Jiuyang Tang, Xiang Zhao*, Each Fake News Is Fake in Its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News Detection, Proceedings of the 39th AAAI Conference on Artificial Intelligence, vol. 39, no. 1, pp. 228–236, 2025.

• Xiaofan Zheng, Minnan Luo*, Xinghao Wang, Unveiling Fake News with Adversarial Arguments Generated by Multimodal Large Language Models, Proceedings of the 31st International Conference on Computational Linguistics, pp. 7862–7869, 2025.

• Chengyou Jia, Changliang Xia, Zhuohang Dang, Weijia Wu, Hangwei Qian, Minnan Luo*, ChatGen: Automatic Text-to-Image Generation from FreeStyle Chatting, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

• Herun Wan, Minnan Luo*, Zhihui Li, Yang Wang, TeST: Temporal–spatial separated transformer for temporal action localization, Neurocomputing, vol. 614, pp. 128688, 2025.

2024

• Zhi Zeng, Minnan Luo*, Xiangzheng Kong, Huan Liu, Hao Guo, Hao Yang, Zihan Ma, Xiang Zhao, Mitigating World Biases: A Multimodal Multi-View Debiasing Framework for Fake News Video Detection, Proceedings of the 32nd ACM International Conference on Multimedia, 2024.

• Chengyou Jia, Minnan Luo*, Xiaojun Chang, Zhuohang Dang, Mingfei Han, Mengmeng Wang, Guang Dai, Sizhe Dang, Jingdong Wang, Generating Action-conditioned Prompts for Open-vocabulary Video Action Recognition, Proceedings of the 32nd ACM International Conference on Multimedia, pp. 4640–4649, 2024.

• Lijing Zheng, Jihong Wang, Huan Liu, Minnan Luo*, Disentangled Counterfactual Graph Augmentation Framework for Fair Graph Learning with Information Bottleneck, Machine Learning and Knowledge Discovery in Databases, pp. 387–405, 2024.

• Wujiang Xu, Xuying Ning, Wenfang Lin, Mingming Ha, Qiongxu Ma, Qianqiao Liang, Xuewen Tao, Linxun Chen, Bing Han, Minnan Luo*, Towards Open-World Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach, Machine Learning and Knowledge Discovery in Databases, pp. 161–179, 2024.

• Zihan Ma, Minnan Luo*, Hao Guo, Zhi Zeng, Yiran Hao, Xiang Zhao, Event-Radar: Event-driven Multi-View Learning for Multimodal Fake News Detection, Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, pp. 5809–5821, 2024.

• Zihan Ma, Huan Liu*, Zhi Zeng, Hao Guo, Xiang Zhao, Minnan Luo, Learning Multimodal Attention Mixed with Frequency Domain Information as Detector for Fake News Detection, Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6, 2024.

• Herun Wan, Ningnan Wang, Xiang Zhao, Rui Li, Hui Yang, Minnan Luo*, FNDPro: Evaluating the Importance of Propagations during Fake News Spread, International Conference on Database Systems for Advanced Applications, pp. 52–67, 2024.

• Chenxi Zhu, Haotian Gao, Yuxiao Duan, Guo Hao, Minnan Luo*, Xiang Zhao*, OSPC: OCR-Assisted VLM for Zero-Shot Harmful Meme Detection, Companion Proceedings of the ACM Web Conference 2024, pp. 1904–1907, 2024.

• Zhuohang Dang, Minnan Luo*, Chengyou Jia, Guang Dai, Xiaojun Chang, Jingdong Wang, Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation, Proceedings of the 38th AAAI Conference on Artificial Intelligence, vol. 38, no. 2, pp. 1463–1471, 2024.

• Chengyou Jia, Minnan Luo*, Zhuohang Dang, Guang Dai, Xiaojun Chang, Mengmeng Wang, Jingdong Wang, SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-Form Layout-to-Image Generation, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Article No. 276, 2024.

• Zijian Cai, Zhaoxuan Tan, Zhenyu Lei, Zifeng Zhu, Hongrui Wang, Qinghua Zheng, Minnan Luo*, LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection, Proceedings of the 17th ACM International Conference on Web Search and Data Mining, pp. 57–66, 2024.

• Herun Wan, Shangbin Feng, Zhaoxuan Tan, Heng Wang, Yulia Tsvetkov, Minnan Luo*, DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection, Findings of the Association for Computational Linguistics: ACL 2024, pp. 2637–2667, 2024.

• Shangbin Feng, Herun Wan, Ningnan Wang, Zhaoxuan Tan, Minnan Luo, Yulia Tsvetkov, What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection, Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 3580–3601, 2024.

• Haochen Han, Qinghua Zheng, Guang Dai, Minnan Luo*, Jingdong Wang, Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 26679–26688, 2024.

• Caixia Yan, Xiaojun Chang, Zhihui Li, Lina Yao, Minnan Luo, Qinghua Zheng*，Masked Distillation Advances Self-Supervised Transformer Architecture Search, The International Conference on Learning Representations, 2024.

• Chengyou Jia, Minnan Luo*, Zhuohang Dang, Guang Dai, Xiaojun Chang, Jingdong Wang, PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement, IEEE Transactions on Circuits and Systems for Video Technology, 2024.

• Zhuohang Dang, Minnan Luo*, Chengyou Jia, Guang Dai, Jihong Wang, Xiaojun Chang, Jingdong Wang, Disentangled Representation Learning With Transmitted Information Bottleneck, IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 12, pp. 13297–13310, 2024.

• Zhuohang Dang, Minnan Luo*, Jihong Wang, Chengyu Jia, Caixia Yan, Guang Dai, Xiaojun Chang, Qinghua Zheng, Disentangled Generation With Information Bottleneck for Enhanced Few-Shot Learning, IEEE Transactions on Image Processing, vol. 33, pp. 3520–3535, 2024.

• Haochen Han, Qinghua Zheng*, Minnan Luo, Kaiyao Miao, Feng Tian, Yan Chen, Noise-Tolerant Learning for Audio-Visual Action Recognition, IEEE Transactions on Multimedia, vol. 26, pp. 7761–7774, 2024.

• Yixiang Dong, Minnan Luo*, Jundong Li, Ziqi Liu, Qinghua Zheng, Semi-Supervised Graph Contrastive Learning with Virtual Adversarial Augmentation, IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4232–4244, 2024.

• Jihong Wang, Minnan Luo*, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng, Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective, IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4290–4303, 2024.

2023

• Shujie Yang, Binchi Zhang, Shangbin Feng, Zhanxuan Tan, Qinghua Zheng, Jun Zhou, Minnan Luo*, AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach, Proceedings of the 2023 Chinese Intelligent Automation Conference, pp. 542–552, 2023.

• Jihong Wang, Minnan Luo*, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng, Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2349–2360, 2023.

• Yuhan Liu, Zhaoxuan Tan, Heng Wang, Shangbin Feng, Qinghua Zheng, Minnan Luo*, BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 485–495, 2023.

• Chengyou Jia, Minnan Luo*, Zhuohang Dang, Xiaojun Chang, Qinghua Zheng, Towards Real-Time Person Search with Invariant Feature Learning, Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1–5, 2023.

• Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo*, KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion, Proceedings of the ACM Web Conference 2023, pp. 2548–2559, 2023.

• Heng Wang, Wenqian Zhang, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Qinghua Zheng, Minnan Luo*, Detecting Spoilers in Movie Reviews with External Movie Knowledge and User Networks, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 16035–16050, 2023.

• Zhaoxuan Tan, Shangbin Feng, Melanie Sclar, Herun Wan, Minnan Luo*, Yejin Choi, Yulia Tsvetkov, BotPercent: Estimating Bot Populations in Twitter Communities, Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 14295–14312, 2023.

• Haochen Han, Kaiyao Miao, Qinghua Zheng, Minnan Luo*, Noisy Correspondence Learning With Meta Similarity Correction, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7517–7526, 2023.

• Zhenyu Lei, Herun Wan, Wenqian Zhang, Shangbin Feng, Zilong Chen, Jundong Li, Qinghua Zheng, Minnan Luo*, BIC: Twitter Bot Detection with Text-Graph Interaction and Semantic Consistency, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pp. 10326-10340, 2023.

• Chengyou Jia, Minnan Luo*, Caixia Yan, Linchao Zhu, Xiaojun Chang, Qinghua Zheng, Collaborative Contrastive Refining for Weakly Supervised Person Search, IEEE Transactions on Image Processing, vol. 32, pp. 4951–4963, 2023.

• Chenxu Wang, Minnan Luo*, Zhen Peng, Yixiang Dong, Huaping Liu, Heterogeneous graph attention network with motif clique, Neurocomputing, vol. 555, pp. 126608, 2023.

• Zhenfei Luo, Yixiang Dong, Qinghua Zheng, Huan Liu, Minnan Luo*, Dual-channel graph contrastive learning for self-supervised graph-level representation learning, Pattern Recognition, 2023.

• Zhuohang Dang, Minnan Luo*, Chengyou Jia, Caixia Yan, Xiaojun Chang, Qinghua Zheng, Counterfactual Generation Framework for Few-Shot Learning, IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 8, pp. 3747–3758, 2023.

2022

• Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng*, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo*, TwiBot-22: Towards Graph-Based Twitter Bot Detection, Advances in Neural Information Processing Systems, vol. 35, pp. 35254–35269, 2022.

• Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo*, GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search, Proceedings of the 31st ACM International Conference on Information and Knowledge Management, pp. 520–529, 2022.

• Shangbin Feng, Zhaoxuan Tan, Zilong Chen, Ningnan Wang, Peisheng Yu, Qinghua Zheng, Xiaojun Chang, Minnan Luo*, PAR: Political Actor Representation Learning with Social Context and Expert Knowledge, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 12022–12036, 2022.

• Shangbin Feng, Zhaoxuan Tan, Rui Li, Minnan Luo*, Heterogeneity-aware Twitter Bot Detection with Relational Graph Transformers, Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 4, pp. 3977-3985, 2022.

• Weifan Wang, Xiaocheng Cheng, Ziqi Liu, Yu Lin, Yue Shen, Binbin Hu, Zhiqiang Zhang, Xiaodong Zeng, Jun Zhou*, Jinjie Gu, Minnan Luo, Intent Mining: A Social and Semantic Enhanced Topic Model for Operation-Friendly Digital Marketing, 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 3254–3267, 2022.

• Wenqian Zhang, Shangbin Feng, Zilong Chen, Zhenyu Lei, Jundong Li, Minnan Luo*, KCD: Knowledge walks and textual cues enhanced political perspective detection in news media, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 4129–4140, 2022.

• Zhen Peng, Yixiang Dong, Minnan Luo*, Xiao-Ming Wu, Qinghua Zheng, A new self-supervised task on graphs: Geodesic distance prediction, Information Sciences, vol. 607, pp. 1195–1210, 2022.

• Lingling Zhang, Xiaojun Chang*, Jun Liu, Minnan Luo, Zhihui Li, Lina Yao, Alex Hauptmann, TN-ZSTAD: Transferable Network for Zero-Shot Temporal Activity Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 3, pp. 3848-3861, 2023.

• Xiang Zhao; Weixin Zeng; Jiuyang Tang; Xinyi Li; Minnan Luo; Qinghua Zheng; Toward Entity Alignment in the Open World: An Unsupervised Approach with Confidence Modeling, Data Science and Engineering, 2022, 7: 16-29.

• Zhen Peng; Minnan Luo*; Wenbing Huang*; Jundong Li; Qinghua Zheng; Fuchun Sun; Junzhou Huang; Learning Representations by Graphical Mutual Information Estimation and Maximization, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.

• Caixia Yan; Xiaojun Chang; Minnan Luo; Huan Liu; Xiaoqin Zhang*; Qinghua Zheng; Semantics-Guided Contrastive Network for Zero-Shot Object detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.

2021

• Shangbin Feng, Herun Wan, Ningnan Wang, Minnan Luo*, BotRGCN: Twitter bot detection with relational graph convolutional networks, Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 236-239, 2021.
• Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo*, Satar: A self-supervised approach to twitter account representation learning and its application in bot detection, Proceedings of the 30th ACM International Conference on Information & Knowledge Management(CIKM), pp. 3808-3817, 2021.
• Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo*, Twibot-20: A comprehensive twitter bot detection benchmark, Proceedings of the 30th ACM International Conference on Information & Knowledge Management(CIKM), pp.4485-4494, 2021.
• Weixin Zeng, Xiang Zhao, Jiuyang Tang, Xinyi Li, Minnan Luo, Qinghua Zheng, Towards entity alignment in the open world: an unsupervised approach, International Conference on Database Systems for Advanced Applications, pp. 272-289, 2021.
• Minnan Luo; Xiaojun Chang*; Chen Gong; Reliable shot identification for complex event detection via visual-semantic embedding, Computer Vision and Image Understanding, 2021, 213:103300.

2020

• Ning Wang, Minnan Luo*, Kaize Ding, Lingling Zhang, Jundong Li, and Qinghua Zheng. Graph Few-shot Learning with Attribute Matching. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management(CIKM), pp. 1545-1554. 2020.
• Zhen Peng, Wenbing Huang*, Minnan Luo*, Qinghua Zheng, Yu Rong, Tingyang Xu, Junzhou Huang, Graph Representation Learning via Graphical Mutual Information Maximization, The Web Conference (WWW), 2020.
• Lingling Zhang, Xiaojun Chan*, Jun Liu, Minnan Luo, Sen Wang, Zongyuan Ge, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
• Wang, Weifan, Minnan Luo*, Yan, Caixia, Wang, Meng, Zhao Xiang, Zheng, Qinghua, Cross-Graph Representation Learning for Unsupervised Graph Alignment, International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
• Yuzhe Zhang, Chen Chen, Minnan Luo*, Jundong Li, Caixia Yan, Qinghua Zheng, Unsupervised Hierarchical Feature Selection on Networked Data, International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
• Huan Liu*; Qinghua Zheng; Minnan Luo; Xiaojun Chang; Caixia Yan; Lina Yao; Memory transformation networks for weakly supervised visual classification, 2020, Knowledge-Based Systems, 210: 106432.
• Caixia Yan; Xiaojun Chang; Minnan Luo; Qinghua Zheng; Xiaoqin Zhang*; Zhihui Li*; Feiping Nie; Self-weighted robust LDA for multiclass classification with edge classes, ACM Transactions on Intelligent Systems and Technology, 2020, 12: 1-19.
• Lingling Zhang; Xiaojun Chang; Jun Liu; Minnan Luo*; Mahesh Prakash; Alexander G Hauptmann; Few-shot activity recognition with cross-modal memory network, Pattern Recognition, 2020, 108: 107348.
• Zhongping Lin; Minnan Luo*; Zhen Peng; Jundong Li; Qinghua Zheng; Nonlinear feature selection on attributed networks, Neurocomputing, 2020, 410: 161-173.
• Luguo Xue; Yan Chen; Minnan Luo*; Zhen Peng; Jun Liu; An anomaly detection framework for time-evolving attributed networks, Neurocomputing, 2020, 407: 39-49.
• Jihong Wang; Minnan Luo*; Fnu Suya; Jundong Li; Zijiang Yang; Qinghua Zheng; Scalable attack on graph data by injecting vicious nodes, Data Mining and Knowledge Discovery 34, no. 5 (2020): 1363-1389.
• Zhen Peng; Minnan Luo*; Jundong Li; Luguo Xue; Qinghua Zheng; A Deep Multi-View Framework for Anomaly Detection on Attributed Networks, IEEE Transactions on Knowledge and Data Engineering (2020).
• Caixia Yan; Qinghua Zheng; Xiaojun Chang; Minnan Luo; Chung-Hsing Yeh; Alexander G. Hauptman; Semantics-preserving graph propagation for zero-shot object detection, IEEE Transactions on Image Processing, 2020, 29: 8163-8176.
• Yixiang Dong; Minnan Luo*; Jundong Li; Deng Cai; Qinghua Zheng; LookCom: Learning Optimal Network for Community Detection, IEEE Transactions on Knowledge and Data Engineering, 2020.
• Huan Liu*; Lina Yao; Qinghua Zheng; Minnan Luo; Hongke Zhao; Yanzhang Lyu; Dual-stream Generative Adversarial Networks for Distributionally Robust Zero-shot Learning, Information Sciences, 2020, 519: 407-422. 
• Gang Wei; Minnan Luo*; Huan Liu; Donghui Zhang; Qinghua Zheng; Progressive Generative Adversarial Networks with Reliable Sample Identification, Pattern Recognition Letters, 2020, 130: 91-98.

2019及之前

• Zhen Peng, Minnan Luo*,Jundong Li, Chen Chen, Qinghua Zheng, Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search , International Conference on Database Systems for Advanced Applications (DASFAA), 2019.
• Luguo Xue, Minnan Luo*, Zhen Peng, Jundong Li, Yan Chen*, Jun Liu, Anomaly Detection in Time-Evolving Attributed Networks , 24th International Conference on Database Systems for Advanced Applications (DASFAA), 2019. 
• Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander Hauptmann,  Qinghua Zheng, Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling, In Proceedings of the 31th Association for the Advancement of Artificial Intelligence (AAAI), 2017.
• Huan Liu, Qinghua Zheng, Minnan Luo, Dingwen Zhang, Xiaojun Chang, Cheng Deng, How Unlabeled Web Videos Help Complex Event Detection? In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.
• 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. 
• Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander Hauptmann, Qinghua Zheng, Avoiding Optimal Mean Robust PCA/2DPCA with Non-greedy L1-norm Maximization, In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
• Minnan Luo, Fuchun Sun, Huaping Liu, Sparse Fuzzy c-regression Models with Application to T-S Fuzzy Systems Identification. In Proceedings of IEEE International Conference on Fuzzy Systems, 2014.
• Minnan Luo, Fuchun Sun, Huaping Liu, A Dynamic T-S Fuzzy Systems Identification Algorithm based on Sparsity Regularization, In Proceedings of IEEE International Symposium on Intelligent Control, 2012.
• Fuchun Sun, Jin Yang, Minnan Luo, Huaping Liu, Optimal Necessary Conditions for General SISO Mamdani Fuzzy Systems as Function Approximators within a Given Accuracy, In Proceedings of IEEE International Conference on Fuzzy Systems, 2011.
• Minnan Luo; Caixia Yan; Qinghua Zheng; Xiaojun Chang; Ling Chen; Feiping Nie*; Discrete Multi-Graph Clustering , IEEE Transactions on Image Processing, 2019, 28(9): 4701-4712.
• 刘欢; 郑庆华; 罗敏楠; 赵洪科; 肖阳; 吕彦章; 基于跨域对抗学习的零样本分类, 计算机研究与发展, 2019, 56(12): 2521-2535.
• Qichao Xu; Zhou Su*; Qinghua Zheng; Minnan Luo; Bo Dong; Kuan Zhang; Game Theoretical Secure Caching Scheme in Multihoming Edge Computing-Enabled Heterogeneous Networks , IEEE Internet of Things Journal, 2019, 6(3): 4536-4546.
• Lingling Zhang; Minnan Luo*; Jun Liu; Xiaojun Chang; Yi Yang; Alexander G. Hauptmann; Deep Top-k Ranking for Image–Sentence Matching, IEEE Transactions on Multimedia, 2019, 22(3): 775-785.
• Lingling Zhang*; Jun Liu; Minnan Luo; Xiaojun Chang; Qinghua Zheng; Alexander G. Hauptmann; Scheduled Sampling for One-shot Learning via Matching Network , Pattern Recognition, 2019, 96: 0-106962.
• Chunfang Liu; Wenbing Huang; Fuchun Sun*; Minnan Luo; Chuanqi Tan; LDS-FCM: A Linear Dynamical System Based Fuzzy C-Means Method for Tactile Recognition , IEEE Transactions on Fuzzy Systems, 2019, 27(1): 72-83.
• Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, Deep Semisupervised Zero-Shot Learning with Maximum Mean Discrepancy, Neural computation, 2018, 30(5): 1426-1447.
• Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G Hauptmann, Qinghua Zheng, Adaptive Unsupervised Feature Selection with Structure Regularization, IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(4): 944-956.
• Minnan Luo, Xiaojun Chang, Liqiang Nie, Yi Yang, Alexander G Hauptmann, Qinghua Zheng, An Adaptive Semi-supervised Feature Analysis for Video Semantic Recognition, IEEE Transactions on Cybernetics, 2018, 48(2): 648-660.
• Lingling Zhang, Minnan Luo, Zhihui Li, Feiping Nie, Huaxiang Zhang, Jun Liu, Qinghua Zheng, Large-Scale Robust Semi-supervised Classification, IEEE Transactions on Cybernetics, 2018.
• Caixia Yan, Minnan Luo, Huan Liu, Zhihui Li, Qinghua Zheng, Top-k Multi-class SVM Using Multiple Features, 2018, 432: 479-494.
• Qichao Xu, Zhou Su, Qinghua Zheng, Minnan Luo, Bo Dong, Secure Content Delivery with Edge Nodes to Save Caching Resources for Mobile Users in Green Cities, IEEE Transactions on Industrial Informatics, 2018, 14(6): 2550-2559.
• Minnan Luo, Xiaojun Chang, Yi Yang, Liqiang Nie, Alexander G Hauptmann, Qinghua Zheng, Simple to Complex Cross-modal Learning to Rank, Computer Vision and Image Understanding, 2017, 163: 67-77.
• Minnan Luo, Xiaojun Chang, Yi Yang, Liqiang Nie, Alexander G Hauptmann, Qinghua Zheng, Avoiding Optimal Mean L21-Norm Maximization-Based Robust PCA for Reconstruction, Neural computation, 2017, 29(4): 1124-1150.
• Lingyun Song, Jun Liu, Minnan Luo, Buyue Qian, Kuan Yang, Sparse Relational Topical Coding on Multi-modal Data, Pattern Recognition, 2017, 72: 368-380.
• Minnan Luo, Lingling Zhang, Jun Liu, Jun Guo, Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, Neurocomputing, 2017, 261: 164-170.
• Caixia Yan, Minnan Luo*, Wenhe Liu, Qinghua Zheng, Robust Dictionary Learning with Graph Regularization for Unsupervised Person Re-identification, Multimedia Tools and Applications, 2018, 77(3): 3553-3577.
• Lingyun Song, Minnan Luo*, Jun Liu, Lingling Zhang, Buyue Qian, Max Haifei Li, Qinghua Zheng, Sparse Multi-modal Topical Coding for Image Annotation, Neurocomputing, 2016, 214: 162-174.
• Hengshan Zhang, Qinghua Zheng, Ting Liu, Zijiang Yang, Minnan Luo, Yu Qu, Improving Linguistic Pairwise Comparison Consistency via Linguistic Discrete Regions, IEEE Transactions on Fuzzy Systems, 2016, 24(3): 600-614.
• Minnan Luo, Fuchun Sun, Huaping Liu, Dynamic T‐S Fuzzy Systems Identification Based on Sparse Regularization, Asian Journal of Control, 2015, 17(1): 274-283.
• Minnan Luo, Fuchun Sun, Huaping Liu, Joint Block Structure Sparse Representation for Multi-input–multi-output (MIMO) T–S Fuzzy System Identification, IEEE Transactions on Fuzzy Systems, 2014, 22(6): 1387-1400.
• Minnan Luo, Fuchun Sun, Huaping Liu, Zhijun Li, A Novel T–S fuzzy Systems Identification with Block Structured Sparse Representation, Journal of the Franklin Institute, 2014, 351(7): 3508-3523.
• Minnan Luo, Fuchun Sun, Huaping Liu, Hierarchical Structured Sparse Representation for T–S Fuzzy Systems Identification, IEEE Transactions on Fuzzy Systems, 2013, 21(6): 1032-1043.
• Minnan Luo, Yongming Li, Fuchun Sun, Huaping Liu, A New Algorithm for Testing Diagnosability of Fuzzy Discrete Event Systems, Information Sciences, 2012, 185(1): 100-113.