More information can be found in my Google Scholar profile.
* denotes equal contributions.
Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution
Haiyan Zhao, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, Mengnan Du
arXiv:2410.00153, 2024 [Website]
Towards Uncovering How Large Language Model Works: An Explainability Perspective
Haiyan Zhao, Fan Yang, Bo Shen, Himabindu Lakkaraju, Mengnan Du
arXiv:2402.10688, 2024
Quantifying Multilingual Performance of Large Language Models Across Languages
Zihao Li, Yucheng Shi, Zirui Liu, Fan Yang, Ali Payani, Ninghao Liu, Mengnan Du
arXiv:2404.11553, 2024
Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du
arXiv:2411.05316, 2024 [Code] [Website]
Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era
Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu
arXiv:2403.08946, 2024 [Code]
Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning
Dong Shu, Mengnan Du
AAAI-25 Student Abstract (Oral Presentation), 2025 [Code]
Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?
Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang
COLING, 2025 [Code] [Website]
Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning
Jingyu Hu, Weiru Liu, Mengnan Du
EMNLP (Main Track), 2024 [Code] [Website]
The Impact of Reasoning Step Length on Large Language Models
Mingyu Jin, Qinkai Yu, Dong shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du
ACL (Findings Track), 2024 [Code]
ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction
Mingyu Jin, Haochen Xue, Zhenting Wang, Boming Kang, Ruosong Ye, Kaixiong Zhou, Mengnan Du, Yongfeng Zhang
COLM, 2024 [Code] [Website]
LawLLM: Law Large Language Model for the US Legal System
Dong Shu, Haoran Zhao, Xukun Liu, David Demeter, Mengnan Du, Yongfeng Zhang
CIKM, 2024 [Code] [Website]
Mitigating Shortcuts in Language Models with Soft Label Encoding
Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du
COLING, 2024 [Code]
Unveiling Project-Specific Bias in Neural Code Models
Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Xiaofei Xie, Yi Li, Yang Liu
COLING, 2024
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Mengnan Du, Yongfeng Zhang
ACML, 2024 [Website]
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure
Junyi Ye, Mengnan Du, Guiling Wang
ACML, 2024
Neural Operator for Accelerating Coronal Magnetic Field Model
Yutao Du, Qin Li, Raghav Gnanasambandam, Mengnan Du, Haimin Wang, Bo Shen
IEEE BigData, 2024
LETA: Learning Transferable Attribution for Generic Vision Explainer
Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu
ICML, 2024
Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models
Ruixiang Tang, Yu-Neng Chuang, Xuanting Cai, Mengnan Du, Xia Hu
NAACL (Findings Track), 2024
Enhancing Fairness in In-Context Learning: Prioritizing Minority Samples in Demonstrations
Jingyu Hu, Mengnan Du
ICLR Tiny Papers Track, 2024
Fair Machine Learning in Healthcare: A Survey
Qizhang Feng, Mengnan Du, Na Zou, and Xia Hu
IEEE Transactions on Artificial Intelligence (TAI), 2024
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
TPAMI, 2024
Mitigating Social Biases of Pre-trained Language Models via Contrastive Self-Debiasing with Double Data Augmentation
Yingji Li, Mengnan Du, Rui Song, Xin Wang, Mingchen Sun, Ying Wang
The journal of Artificial Intelligence (AIJ), 2024
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing
Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He
TKDD, 2024
When Search Engine Services meet Large Language Models: Visions and Challenges
Haoyi Xiong, Jiang Bian, Yuchen Li, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal
Accepted by IEEE Transactions on Services Computing (TSC), 2024
Mitigating Relational Bias on Knowledge Graphs
Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu
TKDD, 2024
Explaining Time Series via Contrastive and Locally Sparse Perturbations
Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen
ICLR, 2024
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
Jingyu Hu, Jun Hong, Mengnan Du, Weiru Liu
Second AEQUITAS Workshop on Fairness and Bias in AI, 2024 [Poster]
Explainability for Large Language Models: A Survey
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
ACM Transactions on Intelligent Systems and Technology (TIST) [Github]
Shortcut Learning of Large Language Models in Natural Language Understanding
Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu
Communications of the ACM (CACM), 2023
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding
Mengnan Du, Subho Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu and Ahmed Hassan Awadallah
The 17th Annual Meeting of the European chapter of the Association for Computational Linguistics (EACL), 2023
Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases
Yingji Li, Mengnan Du, Xin Wang and Ying Wang
The 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Fairness via Group Contribution Matching
Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu
The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023
FAIRER: Fairness as Decision Rationale Alignment
Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu
The 40th International Conference on Machine Learning (ICML), 2023
Black-box Backdoor Defense via Zero-shot Image Purification
Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Ninghao Liu
Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS), 2023
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models
Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, Himabindu Lakkaraju, Haoyi Xiong
NeurIPS Datasets and Benchmarks track, 2023
Deep Serial Number: Computational Watermarking for DNN Intellectual Property Protection
Ruixiang Tang, Mengnan Du, and Xia Hu
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2023
Mitigating Algorithmic Bias with Limited Annotations
Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Hu
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2023
XGBD: Explanation-Guided Graph Backdoor Detection
Zihan Guan, Mengnan Du, Ninghao Liu
26th European Conference on Artificial Intelligence (ECAI), 2023
Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks
Zihan Guan, Lichao Sun, Mengnan Du, Ninghao Liu
Conference on Information and Knowledge Management (CIKM), 2023
Exposing Model Theft: A Robust and Transferable Watermark for Thwarting Model Extraction Attacks
Ruixiang Tang, Hongye Jin, Mengnan Du, Curtis Wigington, Rajiv Jain, Xia Hu
Conference on Information and Knowledge Management (CIKM), short paper, 2023
Error Detection on Knowledge Graphs with Triple Embedding
Yezi Liu, Qinggang Zhang, Mengnan Du, Xiao Huang, and Xia Hu
The 31st European Signal Processing Conference (EUSIPCO), 2023
Proportionate Diversification of Top-k LLM Results using Database Queries
Thinh On, Subhodeep Ghosh, Mengnan Du, Senjuti Basu Roy
1st International Workshop on Databases and Large Language Models at VLDB, 2023
Towards Debiasing DNN Models From Spurious Feature Influence
Mengnan Du, Ruixiang Tang, Weijie Fu, and Xia Hu
Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022
Algorithmic Fairness in Machine Learning
Mengnan Du, Lu Cheng, Dejing Dou
Book Chapter, 2022
Accelerating Shapley Explanation via Contributive Cooperator Selection
Guanchu Wang*, Yu-Neng Chuang*, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai and Xia Hu
The 39th International Conference on Machine Learning (ICML), 2022
Learning Disentangled Representations for Time Series
Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Denghui Zhang, Haifeng Chen, Xia Hu
The 28rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022
DEGREE: Decomposition Based Explanation for Graph Neural Networks
Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu
The Tenth International Conference on Learning Representations (ICLR), 2022
Generating Consistent Multimodal Dialogue Responses with Emoji Context Model
Xiangwu Zuo, Xiao Yu, Mengnan Du, Qingquan Song
in 5th International Conference on Artificial Intelligence and Big Data (ICAIBD), 2022
Fairness via Representation Neutralization
Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Hu
Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), 2021 [Code]
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models
Mengnan Du, Varun Manjunatha, Rajiv Jain, Ruchi Deshpande, Franck Dernoncourt, Jiuxiang Gu,
Tong Sun and Xia Hu
North American Chapter of the Association for Computational Linguistics (NAACL), 2021
Towards Structured NLP Interpretation via Graph Explainers
Hao Yuan*, Fan Yang*, Mengnan Du*, Shuiwang Ji, Xia Hu
Applied AI Letters, 2021
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution
Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, and Xia Hu
The 27rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021
Mitigating Gender Bias in Captioning Systems
Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu and Xia Hu
The Web Conference (WWW), 2021 [Code]
A Unified Taylor Framework for Revisiting Attribution Methods
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu
AAAI Conference on Artificial Intelligence (AAAI), 2021
Sub-Architecture Ensemble Pruning in Neural Architecture Search
Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen and Xia Hu
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Differentiated Explanation of Deep Neural Networks with Skewed Distributions
Weijie Fu, Meng Wang, Mengnan Du, Ninghao Liu, Shijie Hao and Xia Hu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 [Code]
Understanding Social Biases behind Location Names in Contextual Word Embedding Models
Fangsheng Wu, Mengnan Du, Chao Fan, Ruixiang Tang, Yang Yang, Ali Mostafavi, Xia Hu
IEEE Transactions on Computational Social Systems (TCSS), 2021
Adversarial Attacks and Defenses: An Interpretation Perspective
Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu and Xia Hu
SIGKDD Explorations, 2021
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation
Fan Yang, Ninghao Liu, Mengnan Du and Xia Hu
SIGKDD Explorations, 2021
Machine Learning Explanations to Prevent Overtrust in Fake News Detection
Sina Mohseni, Fan Yang, Shiva Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, and Eric Ragan
International AAAI Conference on Web and Social Media (ICWSM), 2021
Techniques for Interpretable Machine Learning
Mengnan Du, Ninghao Liu, and Xia Hu
Communications of the ACM (CACM), 2020 Video
Highlighted on the cover page of the January 2020 issue.
Fairness in Deep Learning: A Computational Perspective
Mengnan Du, Fan Yang, Na Zou, and Xia Hu
IEEE Intelligent Systems, 2020
Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder
Mengnan Du*, Shiva Pentyala*, Yuening Li, Xia Hu
The 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020
Learning Credible DNNs via Incorporating Prior Knowledge and Model Local Explanation
Mengnan Du, Ninghao Liu, Fan Yang, and Xia Hu
Knowledge and Information Systems (KAIS), 2020
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks
Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, and Xia Hu
The 26rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020 [Code]
Deep Neural Networks with Knowledge Instillation
Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji and Xia Hu
SIAM International Conference on Data Mining (SDM), 2020
A Deep Learning Approach for Identifying Cancer Survivors Living with Post-Traumatic Stress Disorder on Twitter
Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He and Xia Hu
BMC Medical Informatics and Decision Making (BMC), 2020
Trust Evolution Over Time in Explainable AI for Fake News Detection
Sina Mohseni, Fan Yang, Shiva Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric Ragan
In CHI Workshop on Fair & Responsible AI, 2020
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks
Haofan Wang, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel, Xia
Hu
In IEEE CVPR Workshop on Fair, Data-Efficient and Trusted Computer Vision, 2020 [Code]
Learning Credible Deep Neural Networks with Rationale Regularization
Mengnan Du, Ninghao Liu, Fan Yang, and Xia Hu
IEEE International Conference on Data Mining (ICDM), 2019
Best Paper Candidate.
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition
Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, and Xia Hu
The Web Conference (WWW), 2019 [Code]
Best Paper Candidate.
XFake: Explainable Fake News Detector with Visualizations
Fan Yang*, Shiva Pentyala*, Sina Mohseni*, Mengnan Du*, Hao Yuan*, Rhema Linder, Eric Ragan, Shuiwang Ji and Xia Hu
The Web Conference (WWW), 2019, demo track
Representation Interpretation with Spatial Encoding and Multimodal Analytics
Ninghao Liu, Mengnan Du, Xia Hu
ACM International Conference on Web Search and Data Mining (WSDM), 2019
Multivariate Multi-step Deep Learning Time Series Approach in Forecasting Parkinson’s Disease Future Severity Progression
Nur Hafieza Ismail, Mengnan Du, Diego Martinez and Zhe He
In The 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB), 2019
Identification of Cancer Survivors Living with Post-Traumatic Stress Disorder (PTSD) on Social Media
Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, and Xia Hu
In The World Congress on Medical and Health Informatics (MEDINFO), poster, 2019
SpecAE: Spectral Autoencoder for Anomaly Detection in Attributed Networks
Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, and Na Zou
ACM International Conference on Information and Knowledge Management (CIKM), 2019
INFORMS 2019 Best Refereed Paper Finalists.
Deep Structured Cross-Modal Anomaly Detection
Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu
International Joint Conference on Neural Networks (IJCNN), 2019
Social Media and Psychological Disorder
Nur Hafieza Ismail, Mengnan Du, Xia Hu
Social Web and Health Research, Springer, 2019
Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media
Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, and Xia Hu
In The 4th Interpretable Workshop on Semantics-Powered Data Mining and Analytics (SEPDA), 2019
Supervised Training and Contextually Guided Salient Object Detection
Mengnan Du, Xingming Wu, Weihai Chen, Zhengguo Li
Digital signal processing (DSP), 2017
Exploiting multiple contexts for saliency detection
Mengnan Du, Xingming Wu, Weihai Chen, Jianhua Wang
Journal of Electronic Imaging (JEI), 2017
Salient object detection via region contrast and graph regularization
Xingming Wu, Mengnan Du, Weihai Chen, Jianhua Wang
SCIENCE CHINA Information Sciences, 2016
Exploiting Deep Convolutional Neural Network and Patch-level CRFs for Indoor Semantic Segmentation
Xingming Wu, Mengnan Du, Weihai Chen, Zhengguo Li
in IEEE Conference on Industrial Electronics and Applications (ICIEA), 2016
Fusing region contrast and graph regularization for saliency detection
Mengnan Du, Xingming Wu, Weihai Chen, Jianhua Wang
In Chinese Control and Decision Conference (CCDC), 2015
Attitude control based on complementary filter for two-wheel self-balance car
Guangsheng Liang, Mengnan Du, Zihao Zhou, et al.
Measurement Control Technology, 2015 (in chinese)