Du, Mengnan

23 publications

ICLR 2025 Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution Haiyan Zhao, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, Mengnan Du

AAAI 2025 Comparative Analysis of Demonstration Selection Algorithms for In-Context Learning in Large Language Models (Student Abstract) Dong Shu, Mengnan Du

ICML 2025 Concept-Centric Token Interpretation for Vector-Quantized Generative Models Tianze Yang, Yucheng Shi, Mengnan Du, Xuansheng Wu, Qiaoyu Tan, Jin Sun, Ninghao Liu

ICLR 2025 From Commands to Prompts: LLM-Based Semantic File System for AIOS Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang

CVPR 2025 Invisible Backdoor Attack Against Self-Supervised Learning Hanrong Zhang, Zhenting Wang, Boheng Li, Fulin Lin, Tingxu Han, Mingyu Jin, Chenlu Zhan, Mengnan Du, Hongwei Wang, Shiqing Ma

AAAI 2025 Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages Zihao Li, Yucheng Shi, Zirui Liu, Fan Yang, Ali Payani, Ninghao Liu, Mengnan Du

ICML 2025 Massive Values in Self-Attention Modules Are the Key to Contextual Knowledge Understanding Mingyu Jin, Kai Mei, Wujiang Xu, Mingjie Sun, Ruixiang Tang, Mengnan Du, Zirui Liu, Yongfeng Zhang

ACML 2024 DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure Junyi Ye, Mengnan Du, Guiling Wang

ICLR 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

ACML 2024 Knowledge Graph Large Language Model (KG-LLM) for Link Prediction Dong Shu, Tianle Chen, Mingyu Jin, Chong Zhang, Mengnan Du, Yongfeng Zhang

ICML 2024 TVE: Learning Meta-Attribution for Transferable 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

NeurIPS 2023 $\mathcal{M}^4$: 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 2023 Black-Box Backdoor Defense via Zero-Shot Image Purification Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun, Ninghao Liu

ECML-PKDD 2023 Deep Serial Number: Computational Watermark for DNN Intellectual Property Protection Ruixiang Tang, Mengnan Du, Xia Hu

ICML 2023 FAIRER: Fairness as Decision Rationale Alignment Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu

IJCAI 2023 Fairness via Group Contribution Matching Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu

ECML-PKDD 2023 Mitigating Algorithmic Bias with Limited Annotations Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu

ICML 2022 Accelerating Shapley Explanation via Contributive Cooperator Selection Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Hu

ICLR 2022 DEGREE: Decomposition Based Explanation for Graph Neural Networks Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu

AAAI 2022 Towards Debiasing DNN Models from Spurious Feature Influence Mengnan Du, Ruixiang Tang, Weijie Fu, Xia Hu

AAAI 2021 A Unified Taylor Framework for Revisiting Attribution Methods Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu

NeurIPS 2021 Fairness via Representation Neutralization Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Awadallah, Xia Hu

CVPRW 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