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2020 – today
- 2025
[j21]Qizhang Feng
, Mengnan Du, Na Zou, Xia Ben Hu:
Fair Machine Learning in Healthcare: A Survey. IEEE Trans. Artif. Intell. 6(3): 493-507 (2025)- [j20]Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He:
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing. ACM Trans. Knowl. Discov. Data 19(2): 40:1-40:26 (2025) - [j19]Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu:
Fair-RGNN: Mitigating Relational Bias on Knowledge Graphs. ACM Trans. Knowl. Discov. Data 19(2): 46:1-46:18 (2025) - [c60]Zihao Li, Yucheng Shi, Zirui Liu, Fan Yang, Ali Payani, Ninghao Liu, Mengnan Du:
Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages. AAAI 2025: 28186-28194 - [c59]Dong Shu, Mengnan Du:
Comparative Analysis of Demonstration Selection Algorithms for In-Context Learning in Large Language Models (Student Abstract). AAAI 2025: 29490-29492 - [c58]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:
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers? COLING 2025: 558-573 - [c57]Haiyan Zhao, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, Mengnan Du:
Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution. ICLR 2025 - [c56]Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang:
From Commands to Prompts: LLM-based Semantic File System for AIOS. ICLR 2025 - [c55]Zhenting Wang, Zhizhi Wang, Mingyu Jin, Mengnan Du, Juan Zhai, Shiqing Ma:
Data-centric NLP Backdoor Defense from the Lens of Memorization. NAACL (Findings) 2025: 5713-5731 - [i79]Dong Shu, Haiyan Zhao, Jingyu Hu, Weiru Liu, Lu Cheng, Mengnan Du:
Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability. CoRR abs/2501.01346 (2025) - [i78]Mingyu Jin, Kai Mei, Wujiang Xu, Mingjie Sun, Ruixiang Tang, Mengnan Du, Zirui Liu, Yongfeng Zhang:
Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding. CoRR abs/2502.01563 (2025) - [i77]Zirui He, Haiyan Zhao, Yiran Qiao, Fan Yang, Ali Payani, Jing Ma, Mengnan Du:
SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models. CoRR abs/2502.11356 (2025) - [i76]Zihao Li, Ruixiang Tang, Lu Cheng, Shuaiqiang Wang, Dawei Yin, Mengnan Du:
DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models. CoRR abs/2502.18353 (2025) - [i75]Dong Shu, Xuansheng Wu, Haiyan Zhao, Daking Rai, Ziyu Yao, Ninghao Liu, Mengnan Du:
A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models. CoRR abs/2503.05613 (2025) - 2024
- [j18]Yingji Li, Mengnan Du, Rui Song, Xin Wang, Mingchen Sun, Ying Wang:
Mitigating social biases of pre-trained language models via contrastive self-debiasing with double data augmentation. Artif. Intell. 332: 104143 (2024) - [j17]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding. Commun. ACM 67(1): 110-120 (2024) - [j16]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang:
Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4625-4640 (2024) - [j15]Hua Tang, Chong Zhang, Mingyu Jin, Qinkai Yu, Zhenting Wang, Xiaobo Jin, Yongfeng Zhang, Mengnan Du:
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities. SIGKDD Explor. 26(2): 109-118 (2024) - [j14]Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du:
Explainability for Large Language Models: A Survey. ACM Trans. Intell. Syst. Technol. 15(2): 20:1-20:38 (2024) - [j13]Haoyi Xiong, Jiang Bian, Yuchen Li, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal:
When Search Engine Services Meet Large Language Models: Visions and Challenges. IEEE Trans. Serv. Comput. 17(6): 4558-4577 (2024) - [c54]Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du:
The Impact of Reasoning Step Length on Large Language Models. ACL (Findings) 2024: 1830-1842 - [c53]Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang:
Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models. ACL (Findings) 2024: 3773-3786 - [c52]Dong Shu, Tianle Chen, Mingyu Jin, Chong Zhang, Mengnan Du, Yongfeng Zhang:
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction. ACML 2024: 143-158 - [c51]Junyi Ye, Mengnan Du, Guiling Wang:
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure. ACML 2024: 575-590 - [c50]Jingyu Hu, Jun Hong, Mengnan Du, Weiru Liu:
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups. AEQUITAS@ECAI 2024 - [c49]Bo Shen, Marco Marena, Chenyang Li, Qin Li, Haodi Jiang, Mengnan Du, Jiajun Xu, Haimin Wang:
Deep Computer Vision for Solar Physics Big Data: Opportunities and Challenges [Vision Paper]. IEEE Big Data 2024: 1860-1864 - [c48]Yutao Du, Qin Li, Raghav Gnanasambandam, Mengnan Du, Haimin Wang, Bo Shen:
Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model. IEEE Big Data 2024: 1964-1971 - [c47]Dong Shu, Haoran Zhao, Xukun Liu, David Demeter, Mengnan Du, Yongfeng Zhang:
LawLLM: Law Large Language Model for the US Legal System. CIKM 2024: 4882-4889 - [c46]Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du:
Mitigating Shortcuts in Language Models with Soft Label Encoding. LREC/COLING 2024: 11341-11348 - [c45]Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Junzhe Jiang, Yang Liu:
Unveiling Project-Specific Bias in Neural Code Models. LREC/COLING 2024: 17205-17216 - [c44]Jingyu Hu, Weiru Liu, Mengnan Du:
Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning. EMNLP 2024: 7460-7475 - [c43]Jingyu Hu, Mengnan Du:
Enhancing Fairness in In-Context Learning: Prioritizing Minority Samples in Demonstrations. Tiny Papers @ ICLR 2024 - [c42]Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen:
Explaining Time Series via Contrastive and Locally Sparse Perturbations. ICLR 2024 - [c41]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
TVE: Learning Meta-attribution for Transferable Vision Explainer. ICML 2024 - [c40]Ruixiang Tang, Yu-Neng Chuang, Xuanting Cai, Mengnan Du, Xia Hu:
Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models. NAACL-HLT (Findings) 2024: 4061-4073 - [c39]Fengxiang He, Mengnan Du, Aris Filos-Ratsikas, Lu Cheng, Qingquan Song, Min Lin, John Vines:
AI Driven Online Advertising: Market Design, Generative AI, and Ethics. WWW (Companion Volume) 2024: 1407-1409 - [i74]Haoyi Xiong, Xuhong Li, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du:
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective. CoRR abs/2401.04374 (2024) - [i73]Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du:
The Impact of Reasoning Step Length on Large Language Models. CoRR abs/2401.04925 (2024) - [i72]Jiamin Chen, Xuhong Li, Yanwu Xu, Mengnan Du, Haoyi Xiong:
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training. CoRR abs/2401.08469 (2024) - [i71]Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen:
Explaining Time Series via Contrastive and Locally Sparse Perturbations. CoRR abs/2401.08552 (2024) - [i70]Junyi Ye, Mengnan Du, Guiling Wang:
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure. CoRR abs/2401.15463 (2024) - [i69]Mingyu Jin, Qinkai Yu, Dong Shu, Chong Zhang, Lizhou Fan, Wenyue Hua, Suiyuan Zhu, Yanda Meng, Zhenting Wang, Mengnan Du, Yongfeng Zhang, Yanda Meng:
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System. CoRR abs/2402.00746 (2024) - [i68]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Fan Yang, Mengnan Du, Xuanting Cai, Xia Hu:
Large Language Models As Faithful Explainers. CoRR abs/2402.04678 (2024) - [i67]Haiyan Zhao, Fan Yang, Himabindu Lakkaraju, Mengnan Du:
Opening the Black Box of Large Language Models: Two Views on Holistic Interpretability. CoRR abs/2402.10688 (2024) - [i66]Mingyu Jin, Hua Tang, Chong Zhang, Qinkai Yu, Chengzhi Liu, Suiyuan Zhu, Yongfeng Zhang, Mengnan Du:
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities. CoRR abs/2402.10835 (2024) - [i65]Mingyu Jin, Beichen Wang, Zhaoqian Xue, Suiyuan Zhu, Wenyue Hua, Hua Tang, Kai Mei, Mengnan Du, Yongfeng Zhang:
What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents. CoRR abs/2402.13184 (2024) - [i64]Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Chong Zhang, Mengnan Du, Yongfeng Zhang:
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction. CoRR abs/2403.07311 (2024) - [i63]Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu:
Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era. CoRR abs/2403.08946 (2024) - [i62]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:
Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers? CoRR abs/2404.07066 (2024) - [i61]Zihao Li, Yucheng Shi, Zirui Liu, Fan Yang, Ninghao Liu, Mengnan Du:
Quantifying Multilingual Performance of Large Language Models Across Languages. CoRR abs/2404.11553 (2024) - [i60]Mingyu Jin, Haochen Xue, Zhenting Wang, Boming Kang, Ruosong Ye, Kaixiong Zhou, Mengnan Du, Yongfeng Zhang:
ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction. CoRR abs/2405.06649 (2024) - [i59]Yutao Du, Qin Li, Raghav Gnanasambandam, Mengnan Du, Haimin Wang, Bo Shen:
Neural Operator for Accelerating Coronal Magnetic Field Model. CoRR abs/2405.12754 (2024) - [i58]Hanrong Zhang, Zhenting Wang, Tingxu Han, Mingyu Jin, Chenlu Zhan, Mengnan Du, Hongwei Wang, Shiqing Ma:
Towards Imperceptible Backdoor Attack in Self-supervised Learning. CoRR abs/2405.14672 (2024) - [i57]Haoyi Xiong, Jiang Bian, Yuchen Li, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal:
When Search Engine Services meet Large Language Models: Visions and Challenges. CoRR abs/2407.00128 (2024) - [i56]Chong Zhang, Xinyi Liu, Mingyu Jin, Zhongmou Zhang, Lingyao Li, Zhenting Wang, Wenyue Hua, Dong Shu, Suiyuan Zhu, Xiaobo Jin, Sujian Li, Mengnan Du, Yongfeng Zhang:
When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments. CoRR abs/2407.18957 (2024) - [i55]Dong Shu, Haoran Zhao, Xukun Liu, David Demeter, Mengnan Du, Yongfeng Zhang:
LawLLM: Law Large Language Model for the US Legal System. CoRR abs/2407.21065 (2024) - [i54]Jingyu Hu, Weiru Liu, Mengnan Du:
Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning. CoRR abs/2408.09757 (2024) - [i53]Bo Shen, Marco Marena, Chenyang Li, Qin Li, Haodi Jiang, Mengnan Du, Jiajun Xu, Haimin Wang:
Deep Computer Vision for Solar Physics Big Data: Opportunities and Challenges. CoRR abs/2409.04850 (2024) - [i52]Zhenting Wang, Zhizhi Wang, Mingyu Jin, Mengnan Du, Juan Zhai, Shiqing Ma:
Data-centric NLP Backdoor Defense from the Lens of Memorization. CoRR abs/2409.14200 (2024) - [i51]Daoyang Li, Mingyu Jin, Qingcheng Zeng, Haiyan Zhao, Mengnan Du:
Exploring Multilingual Probing in Large Language Models: A Cross-Language Analysis. CoRR abs/2409.14459 (2024) - [i50]Haiyan Zhao, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, Mengnan Du:
Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution. CoRR abs/2410.00153 (2024) - [i49]Jingyu Hu, Jun Hong, Mengnan Du, Weiru Liu:
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups. CoRR abs/2410.01145 (2024) - [i48]Shan Xie, Man Luo, Chadly Daniel Stern, Mengnan Du, Lu Cheng:
DemoShapley: Valuation of Demonstrations for In-Context Learning. CoRR abs/2410.07523 (2024) - [i47]Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang:
From Commands to Prompts: LLM-based Semantic File System for AIOS. CoRR abs/2410.11843 (2024) - [i46]Dong Shu, Mengnan Du:
Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning. CoRR abs/2410.23099 (2024) - [i45]Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du:
Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation. CoRR abs/2411.05316 (2024) - 2023
- [c38]Yingji Li, Mengnan Du, Xin Wang, Ying Wang:
Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases. ACL (1) 2023: 14254-14267 - [c37]Zihan Guan, Lichao Sun, Mengnan Du, Ninghao Liu:
Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks. CIKM 2023: 608-618 - [c36]Ruixiang Tang, Hongye Jin, Mengnan Du, Curtis Wigington, Rajiv Jain, Xia Hu:
Exposing Model Theft: A Robust and Transferable Watermark for Thwarting Model Extraction Attacks. CIKM 2023: 4315-4319 - [c35]Mengnan Du, Subhabrata Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu, Ahmed Hassan Awadallah:
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding. EACL 2023: 1758-1770 - [c34]Zihan Guan, Mengnan Du, Ninghao Liu:
XGBD: Explanation-Guided Graph Backdoor Detection. ECAI 2023: 932-939 - [c33]Yezi Liu, Qinggang Zhang, Mengnan Du, Xiao Huang, Xia Hu:
Error Detection on Knowledge Graphs with Triple Embedding. EUSIPCO 2023: 1604-1608 - [c32]Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu:
FAIRER: Fairness as Decision Rationale Alignment. ICML 2023: 19471-19489 - [c31]Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu:
Fairness via Group Contribution Matching. IJCAI 2023: 436-445 - [c30]Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, Himabindu Lakkaraju, Haoyi Xiong:
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models. NeurIPS 2023 - [c29]Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun, Ninghao Liu:
Black-box Backdoor Defense via Zero-shot Image Purification. NeurIPS 2023 - [c28]Ruixiang Tang, Mengnan Du, Xia Hu:
Deep Serial Number: Computational Watermark for DNN Intellectual Property Protection. ECML/PKDD (6) 2023: 157-173 - [c27]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. ECML/PKDD (2) 2023: 241-258 - [c26]Thinh On, Subhodeep Ghosh, Mengnan Du, Senjuti Basu Roy:
Proportionate Diversification of Top-k LLM Results using Database Queries. VLDB Workshops 2023 - [i44]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Zirui Liu, Xuanting Cai, Mengnan Du, Xia Ben Hu:
Efficient XAI Techniques: A Taxonomic Survey. CoRR abs/2302.03225 (2023) - [i43]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang:
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. CoRR abs/2303.01506 (2023) - [i42]Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Ninghao Liu:
Black-box Backdoor Defense via Zero-shot Image Purification. CoRR abs/2303.12175 (2023) - [i41]Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu:
DEGREE: Decomposition Based Explanation For Graph Neural Networks. CoRR abs/2305.12895 (2023) - [i40]Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu:
FAIRER: Fairness as Decision Rationale Alignment. CoRR abs/2306.15299 (2023) - [i39]Yingji Li, Mengnan Du, Xin Wang, Ying Wang:
Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases. CoRR abs/2307.01595 (2023) - [i38]Chia-Yuan Chang, Yu-Neng Chuang, Guanchu Wang, Mengnan Du, Zou Na:
DISPEL: Domain Generalization via Domain-Specific Liberating. CoRR abs/2307.07181 (2023) - [i37]Zihan Guan, Mengnan Du, Ninghao Liu:
XGBD: Explanation-Guided Graph Backdoor Detection. CoRR abs/2308.04406 (2023) - [i36]Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang:
A Survey on Fairness in Large Language Models. CoRR abs/2308.10149 (2023) - [i35]Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du:
Explainability for Large Language Models: A Survey. CoRR abs/2309.01029 (2023) - [i34]Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He:
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing. CoRR abs/2309.08375 (2023) - [i33]Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du:
Mitigating Shortcuts in Language Models with Soft Label Encoding. CoRR abs/2309.09380 (2023) - [i32]Hua Tang, Lu Cheng, Ninghao Liu, Mengnan Du:
A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier. CoRR abs/2310.12785 (2023) - [i31]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
LETA: Learning Transferable Attribution for Generic Vision Explainer. CoRR abs/2312.15359 (2023) - 2022
- [j12]Weijie Fu, Meng Wang, Mengnan Du, Ninghao Liu, Shijie Hao, Xia Hu:
Differentiated Explanation of Deep Neural Networks With Skewed Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 44(6): 2909-2922 (2022) - [j11]Fangsheng Wu, Mengnan Du, Chao Fan, Ruixiang Tang, Yang Yang, Ali Mostafavi, Xia Hu:
Understanding Social Biases Behind Location Names in Contextual Word Embedding Models. IEEE Trans. Comput. Soc. Syst. 9(2): 458-468 (2022) - [j10]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Subarchitecture Ensemble Pruning in Neural Architecture Search. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7928-7936 (2022) - [c25]Mengnan Du, Ruixiang Tang, Weijie Fu, Xia Hu:
Towards Debiasing DNN Models from Spurious Feature Influence. AAAI 2022: 9521-9528 - [c24]Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu:
DEGREE: Decomposition Based Explanation for Graph Neural Networks. ICLR 2022 - [c23]Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
Accelerating Shapley Explanation via Contributive Cooperator Selection. ICML 2022: 22576-22590 - [c22]Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Jingchao Ni, Denghui Zhang, Haifeng Chen, Xia Hu:
Towards Learning Disentangled Representations for Time Series. KDD 2022: 3270-3278 - [i30]Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Xiaofei Xie, Yi Li, Yang Liu:
Unveiling Project-Specific Bias in Neural Code Models. CoRR abs/2201.07381 (2022) - [i29]Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
Accelerating Shapley Explanation via Contributive Cooperator Selection. CoRR abs/2206.08529 (2022) - [i28]Qizhang Feng, Mengnan Du, Na Zou, Xia Hu:
Fair Machine Learning in Healthcare: A Review. CoRR abs/2206.14397 (2022) - [i27]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. CoRR abs/2207.10018 (2022) - [i26]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey. CoRR abs/2208.11857 (2022) - [i25]Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu:
Mitigating Relational Bias on Knowledge Graphs. CoRR abs/2211.14489 (2022) - 2021
- [j9]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. IEEE Intell. Syst. 36(4): 25-34 (2021) - [j8]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning credible DNNs via incorporating prior knowledge and model local explanation. Knowl. Inf. Syst. 63(2): 305-332 (2021) - [j7]Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu:
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation. SIGKDD Explor. 23(1): 59-68 (2021) - [j6]Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu:
Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. 23(1): 86-99 (2021) - [c21]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. AAAI 2021: 11462-11469 - [c20]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. ICWSM 2021: 421-431 - [c19]Xu Duan, Jingzheng Wu, Mengnan Du, Tianyue Luo, Mutian Yang, Yanjun Wu:
MultiCode: A Unified Code Analysis Framework based on Multi-type and Multi-granularity Semantic Learning. ISSRE Workshops 2021: 359-364 - [c18]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. KDD 2021: 258-268 - [c17]Mengnan Du, Varun Manjunatha, Rajiv Jain, Ruchi Deshpande, Franck Dernoncourt, Jiuxiang Gu, Tong Sun, Xia Hu:
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models. NAACL-HLT 2021: 915-929 - [c16]Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Ben Hu:
Fairness via Representation Neutralization. NeurIPS 2021: 12091-12103 - [c15]Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu, Na Zou, Xia Hu:
Mitigating Gender Bias in Captioning Systems. WWW 2021: 633-645 - [i24]Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu:
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation. CoRR abs/2101.06930 (2021) - [i23]Mengnan Du, Varun Manjunatha, Rajiv Jain, Ruchi Deshpande, Franck Dernoncourt, Jiuxiang Gu, Tong Sun, Xia Hu:
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models. CoRR abs/2103.06922 (2021) - [i22]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. CoRR abs/2104.06629 (2021) - [i21]Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Denghui Zhang, Haifeng Chen, Xia Hu:
Learning Disentangled Representations for Time Series. CoRR abs/2105.08179 (2021) - [i20]Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Ben Hu:
Fairness via Representation Neutralization. CoRR abs/2106.12674 (2021) - [i19]Mengnan Du, Subhabrata Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu, Ahmed Hassan Awadallah:
What do Compressed Large Language Models Forget? Robustness Challenges in Model Compression. CoRR abs/2110.08419 (2021) - 2020
- [j5]Mengnan Du, Ninghao Liu, Xia Hu:
Techniques for interpretable machine learning. Commun. ACM 63(1): 68-77 (2020) - [j4]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter. BMC Medical Informatics Decis. Mak. 20-S(4): 254 (2020) - [c14]Mengnan Du, Shiva K. Pentyala, Yuening Li, Xia Hu:
Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder. CIKM 2020: 325-334 - [c13]Haofan Wang, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel, Xia Hu:
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks. CVPR Workshops 2020: 111-119 - [c12]Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. KDD 2020: 218-228 - [c11]Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu:
Deep Neural Networks with Knowledge Instillation. SDM 2020: 370-378 - [i18]Ninghao Liu, Mengnan Du, Xia Hu:
Adversarial Machine Learning: An Interpretation Perspective. CoRR abs/2004.11488 (2020) - [i17]Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. CoRR abs/2006.08131 (2020) - [i16]Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu, Xia Hu:
Mitigating Gender Bias in Captioning Systems. CoRR abs/2006.08315 (2020) - [i15]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. CoRR abs/2007.12358 (2020) - [i14]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. CoRR abs/2008.09695 (2020) - [i13]Ruixiang Tang, Mengnan Du, Xia Hu:
Deep Serial Number: Computational Watermarking for DNN Intellectual Property Protection. CoRR abs/2011.08960 (2020)
2010 – 2019
- 2019
- [c10]Nur Hafieza Ismail, Mengnan Du, Diego Martinez, Zhe He:
Multivariate Multi-step Deep Learning Time Series Approach in Forecasting Parkinson's Disease Future Severity Progression. BCB 2019: 383-389 - [c9]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CIKM 2019: 2233-2236 - [c8]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning Credible Deep Neural Networks with Rationale Regularization. ICDM 2019: 150-159 - [c7]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. IJCNN 2019: 1-8 - [c6]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
Identification of Cancer Survivors Living with PTSD on Social Media. MedInfo 2019: 1468-1469 - [c5]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media. SEPDA@ISWC 2019: 48-52 - [c4]Ninghao Liu, Mengnan Du, Xia Hu:
Representation Interpretation with Spatial Encoding and Multimodal Analytics. WSDM 2019: 60-68 - [c3]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. WWW 2019: 383-393 - [c2]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. WWW 2019: 3600-3604 - [i12]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. CoRR abs/1903.11245 (2019) - [i11]Fan Yang, Mengnan Du, Xia Hu:
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning. CoRR abs/1907.06831 (2019) - [i10]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. CoRR abs/1907.07757 (2019) - [i9]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. CoRR abs/1908.03848 (2019) - [i8]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CoRR abs/1908.03849 (2019) - [i7]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning Credible Deep Neural Networks with Rationale Regularization. CoRR abs/1908.05601 (2019) - [i6]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. CoRR abs/1908.08843 (2019) - [i5]Mengnan Du, Shiva K. Pentyala, Yuening Li, Xia Hu:
Towards Generalizable Forgery Detection with Locality-aware AutoEncoder. CoRR abs/1909.05999 (2019) - [i4]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Sub-Architecture Ensemble Pruning in Neural Architecture Search. CoRR abs/1910.00370 (2019) - [i3]Haofan Wang, Mengnan Du, Fan Yang, Zijian Zhang:
Score-CAM: Improved Visual Explanations Via Score-Weighted Class Activation Mapping. CoRR abs/1910.01279 (2019) - 2018
- [c1]Mengnan Du, Ninghao Liu, Qingquan Song, Xia Hu:
Towards Explanation of DNN-based Prediction with Guided Feature Inversion. KDD 2018: 1358-1367 - [i2]Mengnan Du, Ninghao Liu, Qingquan Song, Xia Hu:
Towards Explanation of DNN-based Prediction with Guided Feature Inversion. CoRR abs/1804.00506 (2018) - [i1]Mengnan Du, Ninghao Liu, Xia Hu:
Techniques for Interpretable Machine Learning. CoRR abs/1808.00033 (2018) - 2017
- [j3]Mengnan Du, Xingming Wu, Weihai Chen, Zhengguo Li:
Supervised training and contextually guided salient object detection. Digit. Signal Process. 63: 44-55 (2017) - 2016
- [j2]Xingming Wu, Mengnan Du, Weihai Chen, Jianhua Wang:
Salient object detection via region contrast and graph regularization. Sci. China Inf. Sci. 59(3): 32104:1-32104:14 (2016) - [j1]Mengnan Du, Xingming Wu, Weihai Chen, Jianhua Wang:
Exploiting multiple contexts for saliency detection. J. Electronic Imaging 25(6): 63005 (2016)
Coauthor Index
[j21] [j19] [j17] [c41] [c40] [i68] [c36] [c35] [c33] [c28] [c27] [i44] [i41] [i31] [j12] [j11] [j10] [c25] [c24] [c23] [c22] [i29] [i28] [i27] [i26] [i25] [j9] [j8] [j7] [j6] [c21] [c20] [c18] [c17] [c16] [c15] [i24] [i23] [i22] [i21] [i20] [i19] [j5] [j4] [c14] [c13] [c12] [c11] [i18] [i17] [i16] [i15] [i14] [i13] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [i12] [i11] [i10] [i9] [i7] [i6] [i5] [i4] [c1] [i2] [i1]
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