Publications
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Preprints
- On Catastrophic Inheritance of Large Foundation Models. Hao Chen, Bhiksha Raj, Xing Xie, Jindong Wang. [arxiv]
- CultureLLM: Incorporating Cultural Differences into Large Language Models. Cheng Li, Mengzhou Chen, Jindong Wang, Sunayana Sitaram, Xing Xie. [arxiv]
- SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization. Xixu Hu, Runkai Zheng, Jindong Wang, Cheuk Hang Leung, Qi Wu, Xing Xie. [arxiv]
- PromptBench: A Unified Library for Evaluation of Large Language Models. Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang, Xing Xie. [arxiv]
- ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning. Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji. [arxiv]
- Meta Semantic Template for Evaluation of Large Language Models. Yachuan Liu, Liang Chen, Jindong Wang, Qiaozhu Mei, Xing Xie. [arxiv]
- Frustratingly Easy Model Generalization by Dummy Risk Minimization. Juncheng Wang, Jindong Wang, Xixu Hu, Shujun Wang, Xing Xie. [arxiv]
- EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus. Cheng Li, Jindong Wang, Kaijie Zhu, Yixuan Zhang, Wenxin Hou, Jianxun Lian, Xing Xie. [arxiv]
- PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie. [arxiv] [code]
- Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj. [arxiv]
- Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets. Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, and Marios Savvides. [arxiv]
- Equivariant Disentangled Transformation for Domain Generalization under Combination Shift. Yivan Zhang, Jindong Wang, Xing Xie, and Masashi Sugiyama. [arxiv]
- Learning Invariant Representations across Domains and Tasks. Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, and Tie-Yan Liu. [arxiv]
- Learning to match distributions for domain adaptation. Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, and Tie-Yan Liu. [arxiv]
Books
Papers
2024
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The good, the bad, and why: Unveiling emotions in generative aiInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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DyVal 2: Dynamic Evaluation of Large Language Models by Meta Probing AgentsInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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A General Framework for Learning from Weak SupervisionInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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Selective mixup helps with distribution shifts, but not (only) because of mixupInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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Open-Vocabulary Calibration for Vision-Language ModelsInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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Trustllm: Trustworthiness in large language modelsInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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Position Paper: What Can Large Language Models Tell Us about Time Series AnalysisInternational Conference on Machine Learning (ICML) 2024 | [ arXiv ]
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Supervised Knowledge Makes Large Language Models Better In-context LearnersInternational Conference on Learning Representation (ICLR) 2024 | [ arXiv ]
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Generating Virtual Reality Interaction Data from Out-of-Distribution Desktop Data: An Exploration Using Stroke GesturesThe IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR) 2024 | [ ]
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UP-Net: An Uncertainty-Driven Prototypical Network for Few-Shot Fault DiagnosisIEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2024 | [ ]
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Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided SolutionSIAM Conference on Data Mining (SDM) 2024 | [ arXiv ]
2023
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Out-of-Distribution Generalization in Text Classification: Past, Present, and FutureThe 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023 | [ arXiv ]
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Boosting cross-domain speech recognition with self-supervisionIEEE Transactions on Audio, Speech and Language Processing (TASLP) 2023 | [ arXiv ]
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A mutual learning framework for pruned and quantized networksJournal of Computer Science & Technology 2023 | [ ]
2022
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Hierarchical knowledge amalgamation with dual discriminative feature alignmentInformation Sciences 2022 | [ Website ]
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Local and global alignments for generalizable sensor-based human activity recognitionIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022 | [ HTML ]
2021
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MixSpeech: Data Augmentation for Low-resource Automatic Speech RecognitionIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021 | [ arXiv ]
2020
2019
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DrowsyDet: A Mobile Application for Real-time Driver Drowsiness DetectionUbiquitous Intelligence Computing 2019 | [ ]
2018
2017
2016