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ORCIDJindong Wang 0001
Person information
- affiliation: College of William & Mary, Williamsburg, VA, USA
- affiliation (former): Microsoft Research Asia, Beijing, China
- affiliation (former): Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China
- affiliation (former): Beijing Key Laboratory of Mobile Computing and Pervasive Device, China
- affiliation (former): University of Chinese Academy of Sciences, Beijing, China
Other persons with the same name
- Jindong Wang (aka: Jin-dong Wang) — disambiguation page
- Jindong Wang 0002
![[0000-0002-7641-9014]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-7641-9014")
— Zhengzhou Institute of Information Science and Technology, Zhengzhou, China - Jindong Wang 0003 — Southwest Jiaotong University, China
- Jindong Wang 0004 — Northeastern University, Shenyang, Liaoning, China
- Jindong Wang 0005 — Shandong Computer Science Center, Jinan, Shandong, China
- Jindong Wang 0006 — Tianjin University, Tianjin, China
- Jindong Wang 0007 — PLA Information Engineering University, Zhengzhou, China
- Jindong Wang 0008 — Xi'an Jiaotong University, Xi'an, China
- Jindong Wang 0009 — Northeast Petroleum University, College of Mechanical Science and Engineering, Daqing, China (and 1 more)
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2020 – today
- 2025
[i114]Shudong Liu, Yiqiao Jin, Cheng Li, Derek F. Wong, Qingsong Wen, Lichao Sun, Haipeng Chen, Xing Xie, Jindong Wang:
CultureVLM: Characterizing and Improving Cultural Understanding of Vision-Language Models for over 100 Countries. CoRR abs/2501.01282 (2025)- [i113]Jing Yao, Xiaoyuan Yi, Shitong Duan, Jindong Wang, Yuzhuo Bai, Muhua Huang, Peng Zhang, Tun Lu, Zhicheng Dou, Maosong Sun, Xing Xie:
Value Compass Leaderboard: A Platform for Fundamental and Validated Evaluation of LLMs Values. CoRR abs/2501.07071 (2025) - 2024
- [j31]Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Wei Ye, Haojun Huang, Xiubo Geng, Binxing Jiao, Yue Zhang, Xing Xie:
On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective. IEEE Data Eng. Bull. 47(1): 48-62 (2024) - [j30]Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang:
Exploring Vision-Language Models for Imbalanced Learning. Int. J. Comput. Vis. 132(1): 224-237 (2024) - [j29]Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang, Xing Xie:
PromptBench: A Unified Library for Evaluation of Large Language Models. J. Mach. Learn. Res. 25: 254:1-254:22 (2024) - [j28]Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xiangyang Ji, Qiang Yang, Xing Xie:
Diversify: A General Framework for Time Series Out-of-Distribution Detection and Generalization. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4534-4550 (2024) - [j27]Han Zhu, Gaofeng Cheng, Jindong Wang, Wenxin Hou, Pengyuan Zhang, Yonghong Yan:
Boosting Cross-Domain Speech Recognition With Self-Supervision. IEEE ACM Trans. Audio Speech Lang. Process. 32: 471-485 (2024) - [j26]Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin:
Personalized Federated Learning With Adaptive Batchnorm for Healthcare. IEEE Trans. Big Data 10(6): 915-925 (2024) - [j25]Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie:
A Survey on Evaluation of Large Language Models. ACM Trans. Intell. Syst. Technol. 15(3): 39:1-39:45 (2024) - [j24]Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie:
MetaFed: Federated Learning Among Federations With Cyclic Knowledge Distillation for Personalized Healthcare. IEEE Trans. Neural Networks Learn. Syst. 35(11): 16671-16682 (2024) - [c71]Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, Huajun Chen:
Detoxifying Large Language Models via Knowledge Editing. ACL (1) 2024: 3093-3118 - [c70]Zhuohao Yu, Chang Gao, Wenjin Yao, Yidong Wang, Wei Ye, Jindong Wang, Xing Xie, Yue Zhang, Shikun Zhang:
KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models. ACL (1) 2024: 5967-5985 - [c69]Yiqiao Jin, Minje Choi, Gaurav Verma, Jindong Wang, Srijan Kumar:
MM-SOC: Benchmarking Multimodal Large Language Models in Social Media Platforms. ACL (Findings) 2024: 6192-6210 - [c68]Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash:
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. ACL (Findings) 2024: 7832-7840 - [c67]Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Xiang Li, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides:
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets. CVPR Workshops 2024: 1551-1561 - [c66]Xixu Hu, Runkai Zheng, Jindong Wang, Cheuk Hang Leung, Qi Wu, Xing Xie:
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization. ECCV (54) 2024: 345-362 - [c65]Yiqiao Jin, Qinlin Zhao, Yiyang Wang, Hao Chen, Kaijie Zhu, Yijia Xiao, Jindong Wang:
AgentReview: Exploring Peer Review Dynamics with LLM Agents. EMNLP 2024: 1208-1226 - [c64]Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj:
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. ICLR 2024 - [c63]Yidong Wang, Zhuohao Yu, Wenjin Yao, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang:
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization. ICLR 2024 - [c62]Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, Yue Zhang:
Supervised Knowledge Makes Large Language Models Better In-context Learners. ICLR 2024 - [c61]Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie:
DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks. ICLR 2024 - [c60]Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen:
Position: What Can Large Language Models Tell Us about Time Series Analysis. ICML 2024 - [c59]Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
A General Framework for Learning from Weak Supervision. ICML 2024 - [c58]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c57]Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Xinyi Wang, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xie:
The Good, The Bad, and Why: Unveiling Emotions in Generative AI. ICML 2024 - [c56]Damien Teney, Jindong Wang, Ehsan Abbasnejad:
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. ICML 2024 - [c55]Shuoyuan Wang, Jindong Wang, Guoqing Wang, Bob Zhang, Kaiyang Zhou, Hongxin Wei:
Open-Vocabulary Calibration for Fine-tuned CLIP. ICML 2024 - [c54]Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie:
CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents. ICML 2024 - [c53]Kaijie Zhu, Jindong Wang, Qinlin Zhao, Ruochen Xu, Xing Xie:
Dynamic Evaluation of Large Language Models by Meta Probing Agents. ICML 2024 - [c52]Xu Wang, Cheng Li, Yi Chang, Jindong Wang, Yuan Wu:
NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli. IJCAI 2024: 6504-6512 - [c51]Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Yue Zhang, Neil Gong, Xing Xie:
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. LAMPS@CCS 2024: 57-68 - [c50]Lai Wei, Zhiquan Tan, Chenghai Li, Jindong Wang, Weiran Huang:
Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models. NeurIPS 2024 - [c49]Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xiang Li, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. NeurIPS 2024 - [c48]Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj:
Slight Corruption in Pre-training Data Makes Better Diffusion Models. NeurIPS 2024 - [c47]Cheng Li, Mengzhuo Chen, Jindong Wang, Sunayana Sitaram, Xing Xie:
CultureLLM: Incorporating Cultural Differences into Large Language Models. NeurIPS 2024 - [c46]Cheng Li, Damien Teney, Linyi Yang, Qingsong Wen, Xing Xie, Jindong Wang:
CulturePark: Boosting Cross-cultural Understanding in Large Language Models. NeurIPS 2024 - [c45]Jio Oh, Soyeon Kim, Junseok Seo, Jindong Wang, Ruochen Xu, Xing Xie, Steven Whang:
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models. NeurIPS 2024 - [c44]Wang Lu, Jindong Wang, Yidong Wang, Xing Xie:
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. SDM 2024: 244-252 - [c43]Linping Yuan, Boyu Li, Jindong Wang, Huamin Qu, Wei Zeng:
Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data. VR 2024: 732-742 - [i112]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i111]Lai Wei, Zhiquan Tan, Chenghai Li, Jindong Wang, Weiran Huang:
Large Language Model Evaluation via Matrix Entropy. CoRR abs/2401.17139 (2024) - [i110]Hao Chen, Bhiksha Raj, Xing Xie, Jindong Wang:
On Catastrophic Inheritance of Large Foundation Models. CoRR abs/2402.01909 (2024) - [i109]Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
A General Framework for Learning from Weak Supervision. CoRR abs/2402.01922 (2024) - [i108]Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen:
Position Paper: What Can Large Language Models Tell Us about Time Series Analysis. CoRR abs/2402.02713 (2024) - [i107]Xixu Hu, Runkai Zheng, Jindong Wang, Cheuk Hang Leung, Qi Wu, Xing Xie:
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization. CoRR abs/2402.03317 (2024) - [i106]Cheng Li, Mengzhuo Chen, Jindong Wang, Sunayana Sitaram, Xing Xie:
CultureLLM: Incorporating Cultural Differences into Large Language Models. CoRR abs/2402.10946 (2024) - [i105]Yiqiao Jin, Minje Choi, Gaurav Verma, Jindong Wang, Srijan Kumar:
MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms. CoRR abs/2402.14154 (2024) - [i104]Kaijie Zhu, Jindong Wang, Qinlin Zhao, Ruochen Xu, Xing Xie:
DyVal 2: Dynamic Evaluation of Large Language Models by Meta Probing Agents. CoRR abs/2402.14865 (2024) - [i103]Zhuohao Yu, Chang Gao, Wenjin Yao, Yidong Wang, Wei Ye, Jindong Wang, Xing Xie, Yue Zhang, Shikun Zhang:
KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models. CoRR abs/2402.15043 (2024) - [i102]Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash:
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. CoRR abs/2402.16132 (2024) - [i101]Lizhou Fan, Wenyue Hua, Xiang Li, Kaijie Zhu, Mingyu Jin, Lingyao Li, Haoyang Ling, Jinkui Chi, Jindong Wang, Xin Ma, Yongfeng Zhang:
NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models. CoRR abs/2403.01777 (2024) - [i100]Jio Oh, Soyeon Kim, Junseok Seo, Jindong Wang, Ruochen Xu, Xing Xie, Steven Euijong Whang:
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models. CoRR abs/2403.05266 (2024) - [i99]Hao Chen, Jindong Wang, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj:
Learning with Noisy Foundation Models. CoRR abs/2403.06869 (2024) - [i98]Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, Huajun Chen:
Detoxifying Large Language Models via Knowledge Editing. CoRR abs/2403.14472 (2024) - [i97]Zhuohao Yu, Chang Gao, Wenjin Yao, Yidong Wang, Zhengran Zeng, Wei Ye, Jindong Wang, Yue Zhang, Shikun Zhang:
FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models. CoRR abs/2404.06003 (2024) - [i96]Xu Wang, Cheng Li, Yi Chang, Jindong Wang, Yuan Wu:
NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli. CoRR abs/2405.02814 (2024) - [i95]Cheng Li, Damien Teney, Linyi Yang, Qingsong Wen, Xing Xie, Jindong Wang:
CulturePark: Boosting Cross-cultural Understanding in Large Language Models. CoRR abs/2405.15145 (2024) - [i94]Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj:
Slight Corruption in Pre-training Data Makes Better Diffusion Models. CoRR abs/2405.20494 (2024) - [i93]Millicent Ochieng, Varun Gumma, Sunayana Sitaram, Jindong Wang, Vishrav Chaudhary, Keshet Ronen, Kalika Bali, Jacki O'Neill:
Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios. CoRR abs/2406.00343 (2024) - [i92]Wenyue Hua, Kaijie Zhu, Lingyao Li, Lizhou Fan, Shuhang Lin, Mingyu Jin, Haochen Xue, Zelong Li, Jindong Wang, Yongfeng Zhang:
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities. CoRR abs/2406.02787 (2024) - [i91]Zhiquan Tan, Lai Wei, Jindong Wang, Xing Xie, Weiran Huang:
Can I understand what I create? Self-Knowledge Evaluation of Large Language Models. CoRR abs/2406.06140 (2024) - [i90]Yiqiao Jin, Qinlin Zhao, Yiyang Wang, Hao Chen, Kaijie Zhu, Yijia Xiao, Jindong Wang:
AgentReview: Exploring Peer Review Dynamics with LLM Agents. CoRR abs/2406.12708 (2024) - [i89]Zihao Zhou, Shudong Liu, Maizhen Ning, Wei Liu, Jindong Wang, Derek F. Wong, Xiaowei Huang, Qiufeng Wang, Kaizhu Huang:
Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist. CoRR abs/2407.08733 (2024) - [i88]Minghao Liu, Zonglin Di, Jiaheng Wei, Zhongruo Wang, Hengxiang Zhang, Ruixuan Xiao, Haoyu Wang, Jinlong Pang, Hao Chen, Ankit Shah, Hongxin Wei, Xinlei He, Zhaowei Zhao, Haobo Wang, Lei Feng, Jindong Wang, James Davis, Yang Liu:
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. CoRR abs/2408.11338 (2024) - [i87]Shengzhong Mao, Chaoli Zhang, Yichi Song, Jindong Wang, Xiao-Jun Zeng, Zenglin Xu, Qingsong Wen:
Time Series Analysis for Education: Methods, Applications, and Future Directions. CoRR abs/2408.13960 (2024) - [i86]Liguo Chen, Qi Guo, Hongrui Jia, Zhengran Zeng, Xin Wang, Yijiang Xu, Jian Wu, Yidong Wang, Qing Gao, Jindong Wang, Wei Ye, Shikun Zhang:
A Survey on Evaluating Large Language Models in Code Generation Tasks. CoRR abs/2408.16498 (2024) - [i85]Yijiang Xu, Hongrui Jia, Liguo Chen, Xin Wang, Zhengran Zeng, Yidong Wang, Qing Gao, Jindong Wang, Wei Ye, Shikun Zhang, Zhonghai Wu:
ISC4DGF: Enhancing Directed Grey-box Fuzzing with LLM-Driven Initial Seed Corpus Generation. CoRR abs/2409.14329 (2024) - [i84]Xilong Wang, Hao Fu, Jindong Wang, Neil Zhenqiang Gong:
StringLLM: Understanding the String Processing Capability of Large Language Models. CoRR abs/2410.01208 (2024) - [i83]Cheng Li, May Fung, Qingyun Wang, Chi Han, Manling Li, Jindong Wang, Heng Ji:
MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders. CoRR abs/2410.06845 (2024) - [i82]Yiqiao Jin, Yijia Xiao, Yiyang Wang, Jindong Wang:
Scito2M: A 2 Million, 30-Year Cross-disciplinary Dataset for Temporal Scientometric Analysis. CoRR abs/2410.09510 (2024) - [i81]Hao Chen, Abdul Waheed, Xiang Li, Yidong Wang, Jindong Wang, Bhiksha Raj, Marah I Abdin:
On the Diversity of Synthetic Data and its Impact on Training Large Language Models. CoRR abs/2410.15226 (2024) - [i80]Yue Huang, Zhengqing Yuan, Yujun Zhou, Kehan Guo, Xiangqi Wang, Haomin Zhuang, Weixiang Sun, Lichao Sun, Jindong Wang, Yanfang Ye, Xiangliang Zhang:
Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations? CoRR abs/2410.23426 (2024) - [i79]Yixuan Weng, Minjun Zhu, Guangsheng Bao, Hongbo Zhang, Jindong Wang, Yue Zhang, Linyi Yang:
CycleResearcher: Improving Automated Research via Automated Review. CoRR abs/2411.00816 (2024) - [i78]Tingyuan Zhu, Shudong Liu, Yidong Wang, Derek F. Wong, Han Yu, Takahiro Shinozaki, Jindong Wang:
Learning from "Silly" Questions Improves Large Language Models, But Only Slightly. CoRR abs/2411.14121 (2024) - [i77]Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Jiuxiang Gu, Jindong Wang, Zhe Lin, Bhiksha Raj:
XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation. CoRR abs/2412.01762 (2024) - [i76]Hao Chen, Ze Wang, Xiang Li, Ximeng Sun, Fangyi Chen, Jiang Liu, Jindong Wang, Bhiksha Raj, Zicheng Liu, Emad Barsoum:
SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer. CoRR abs/2412.10958 (2024) - [i75]Zhuohao Yu, Weizheng Gu, Yidong Wang, Zhengran Zeng, Jindong Wang, Wei Ye, Shikun Zhang:
Outcome-Refining Process Supervision for Code Generation. CoRR abs/2412.15118 (2024) - [i74]Jio Oh, Geon Heo, Seungjun Oh, Jindong Wang, Xing Xie, Steven Euijong Whang:
Better Think with Tables: Leveraging Tables to Enhance Large Language Model Comprehension. CoRR abs/2412.17189 (2024) - 2023
- [j23]Wang Lu, Xixu Hu, Jindong Wang, Xing Xie:
FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning. IEEE Data Eng. Bull. 46(1): 52-66 (2023) - [j22]Shuoyuan Wang, Jindong Wang, Huajun Xi, Bob Zhang, Lei Zhang, Hongxin Wei:
Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7(4): 183:1-183:27 (2023) - [j21]Xiaohai Li, Yiqiang Chen, Jindong Wang:
A Mutual Learning Framework for Pruned and Quantized Networks. J. Comput. Sci. Technol. 23(1): 01 (2023) - [j20]Xin Qin, Jindong Wang, Yiqiang Chen, Wang Lu, Xinlong Jiang:
Domain Generalization for Activity Recognition via Adaptive Feature Fusion. ACM Trans. Intell. Syst. Technol. 14(1): 9:1-9:21 (2023) - [j19]Yuxin Zhang, Yiqiang Chen, Jindong Wang, Zhiwen Pan:
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals. IEEE Trans. Knowl. Data Eng. 35(2): 2118-2132 (2023) - [j18]Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. IEEE Trans. Knowl. Data Eng. 35(7): 7178-7191 (2023) - [j17]Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, Philip S. Yu:
Generalizing to Unseen Domains: A Survey on Domain Generalization. IEEE Trans. Knowl. Data Eng. 35(8): 8052-8072 (2023) - [j16]Yuxin Zhang, Jindong Wang, Yiqiang Chen, Han Yu, Tao Qin:
Adaptive Memory Networks With Self-Supervised Learning for Unsupervised Anomaly Detection. IEEE Trans. Knowl. Data Eng. 35(12): 12068-12080 (2023) - [c42]Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, Jindong Wang, Xing Xie, Yue Zhang:
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective. ACL (Findings) 2023: 12731-12750 - [c41]Chao Zhang, Fangzhao Wu, Jingwei Yi, Derong Xu, Yang Yu, Jindong Wang, Yidong Wang, Tong Xu, Xing Xie, Enhong Chen:
Non-IID always Bad? Semi-Supervised Heterogeneous Federated Learning with Local Knowledge Enhancement. CIKM 2023: 3257-3267 - [c40]Linyi Yang, Yaoxian Song, Xuan Ren, Chenyang Lyu, Yidong Wang, Jingming Zhuo, Lingqiao Liu, Jindong Wang, Jennifer Foster, Yue Zhang:
Out-of-Distribution Generalization in Natural Language Processing: Past, Present, and Future. EMNLP 2023: 4533-4559 - [c39]Kaijie Zhu, Xixu Hu, Jindong Wang, Xing Xie, Ge Yang:
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning. ICCV 2023: 4401-4411 - [c38]Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides:
SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning. ICLR 2023 - [c37]Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xing Xie:
Out-of-distribution Representation Learning for Time Series Classification. ICLR 2023 - [c36]Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, Xing Xie:
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning. ICLR 2023 - [c35]Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen:
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning. KDD 2023: 1943-1953 - [c34]Yifan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, Xing Xie:
Domain-Specific Risk Minimization for Domain Generalization. KDD 2023: 3409-3421 - [c33]Jindong Wang, Haoliang Li, Haohan Wang, Sinno Jialin Pan, Xing Xie:
Trustworthy Machine Learning: Robustness, Generalization, and Interpretability. KDD 2023: 5827-5828 - [c32]Wang Lu, Jindong Wang, Yidong Wang, Xing Xie:
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. CDPD 2023: 75-97 - [c31]Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang:
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models. NeurIPS 2023 - [c30]Jindong Wang, Haoliang Li, Sinno Jialin Pan, Xing Xie:
A Tutorial on Domain Generalization. WSDM 2023: 1236-1239 - [i73]Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides:
SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning. CoRR abs/2301.10921 (2023) - [i72]Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxing Jiao, Yue Zhang, Xing Xie:
On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective. CoRR abs/2302.12095 (2023) - [i71]Wang Lu, Xixu Hu, Jindong Wang, Xing Xie:
FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning. CoRR abs/2302.13485 (2023) - [i70]Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang:
Exploring Vision-Language Models for Imbalanced Learning. CoRR abs/2304.01457 (2023) - [i69]Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj:
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. CoRR abs/2305.12715 (2023) - [i68]Linyi Yang, Yaoxiao Song, Xuan Ren, Chenyang Lyu, Yidong Wang, Lingqiao Liu, Jindong Wang, Jennifer Foster, Yue Zhang:
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future. CoRR abs/2305.14104 (2023) - [i67]Damien Teney, Jindong Wang, Ehsan Abbasnejad:
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. CoRR abs/2305.16817 (2023) - [i66]Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie:
PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. CoRR abs/2306.04528 (2023) - [i65]Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen:
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning. CoRR abs/2306.04641 (2023) - [i64]Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang:
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization. CoRR abs/2306.05087 (2023) - [i63]Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie:
A Survey on Evaluation of Large Language Models. CoRR abs/2307.03109 (2023) - [i62]Cheng Li, Jindong Wang, Kaijie Zhu, Yixuan Zhang, Wenxin Hou, Jianxun Lian, Xing Xie:
EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus. CoRR abs/2307.11760 (2023) - [i61]Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xiangyang Ji, Qiang Yang, Xing Xie:
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization. CoRR abs/2308.02282 (2023) - [i60]Juncheng Wang, Jindong Wang, Xixu Hu, Shujun Wang, Xing Xie:
Frustratingly Easy Model Generalization by Dummy Risk Minimization. CoRR abs/2308.02287 (2023) - [i59]Kaijie Zhu, Jindong Wang, Xixu Hu, Xing Xie, Ge Yang:
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning. CoRR abs/2308.02533 (2023) - [i58]Jing Yao, Xiaoyuan Yi, Xiting Wang, Jindong Wang, Xing Xie:
From Instructions to Intrinsic Human Values - A Survey of Alignment Goals for Big Models. CoRR abs/2308.12014 (2023) - [i57]Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj:
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. CoRR abs/2309.17002 (2023) - [i56]Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie:
DyVal: Graph-informed Dynamic Evaluation of Large Language Models. CoRR abs/2309.17167 (2023) - [i55]Yachuan Liu, Liang Chen, Jindong Wang, Qiaozhu Mei, Xing Xie:
Meta Semantic Template for Evaluation of Large Language Models. CoRR abs/2310.01448 (2023) - [i54]Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji:
ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning. CoRR abs/2310.05143 (2023) - [i53]Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, Yidong Wang, Linyi Yang, Jindong Wang, Xing Xie, Zheng Zhang, Yue Zhang:
Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity. CoRR abs/2310.07521 (2023) - [i52]Runxue Bao, Yiming Sun, Yuhe Gao, Jindong Wang, Qiang Yang, Haifeng Chen, Zhi-Hong Mao, Ye Ye:
A Survey of Heterogeneous Transfer Learning. CoRR abs/2310.08459 (2023) - [i51]Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie:
CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents. CoRR abs/2310.17512 (2023) - [i50]Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang:
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models. CoRR abs/2311.01441 (2023) - [i49]Yao Zhu, Yuefeng Chen, Wei Wang, Xiaofeng Mao, Xiu Yan, Yue Wang, Zhigang Li, Wang Lu, Jindong Wang, Xiangyang Ji:
Enhancing Few-shot CLIP with Semantic-Aware Fine-Tuning. CoRR abs/2311.04464 (2023) - [i48]Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Tailin Wu, Yilong Yin, Salman H. Khan, Lina Yao, Tongliang Liu, Kun Zhang:
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation. CoRR abs/2312.07424 (2023) - [i47]Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang, Xing Xie:
PromptBench: A Unified Library for Evaluation of Large Language Models. CoRR abs/2312.07910 (2023) - [i46]Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Xinyi Wang, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xie:
The Good, The Bad, and Why: Unveiling Emotions in Generative AI. CoRR abs/2312.11111 (2023) - [i45]Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, Yue Zhang:
Supervised Knowledge Makes Large Language Models Better In-context Learners. CoRR abs/2312.15918 (2023) - 2022
- [j15]Wang Lu, Jindong Wang, Yiqiang Chen, Sinno Jialin Pan, Chunyu Hu, Xin Qin:
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(2): 65:1-65:19 (2022) - [j14]Renjun Xu, Shuoying Liang, Lanyu Wen, Zhitong Guo, Xinyue Huang, Mingli Song, Jindong Wang, Xiaoxiao Xu, Huajun Chen:
Hierarchical knowledge amalgamation with dual discriminative feature alignment. Inf. Sci. 613: 556-574 (2022) - [j13]Wenxin Hou, Han Zhu, Yidong Wang, Jindong Wang, Tao Qin, Renjun Xu, Takahiro Shinozaki:
Exploiting Adapters for Cross-Lingual Low-Resource Speech Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 30: 317-329 (2022) - [j12]Wang Lu, Jindong Wang, Haoliang Li, Yiqiang Chen, Xing Xie:
Domain-invariant Feature Exploration for Domain Generalization. Trans. Mach. Learn. Res. 2022 (2022) - [c29]Yidong Wang, Bowen Zhang, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki:
Margin Calibration for Long-Tailed Visual Recognition. ACML 2022: 1101-1116 - [c28]Yidong Wang, Hao Wu, Ao Liu, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki, Manabu Okumura, Yue Zhang:
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction. COLING 2022: 7075-7085 - [c27]Wang Lu, Jindong Wang, Yiqiang Chen:
Local and Global Alignments for Generalizable Sensor-Based Human Activity Recognition. ICASSP 2022: 3833-3837 - [c26]Ziqi Zhang, Yuanchun Li, Jindong Wang, Bingyan Liu, Ding Li, Yao Guo, Xiangqun Chen, Yunxin Liu:
ReMoS: Reducing Defect Inheritance in Transfer Learning via Relevant Model Slicing. ICSE 2022: 1856-1868 - [c25]Han Zhu, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan:
Decoupled Federated Learning for ASR with Non-IID Data. INTERSPEECH 2022: 2628-2632 - [c24]Han Zhu, Li Wang, Gaofeng Cheng, Jindong Wang, Pengyuan Zhang, Yonghong Yan:
Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASR. INTERSPEECH 2022: 4870-4874 - [c23]Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang:
USB: A Unified Semi-supervised Learning Benchmark for Classification. NeurIPS 2022 - [c22]Xiaohai Li, Weiwei Dai, Yiqiang Chen, Jindong Wang:
DOPNet: Dynamic Optimized Pruning Net for Model Compression. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 360-367 - [i44]Yuxin Zhang, Jindong Wang, Yiqiang Chen, Han Yu, Tao Qin:
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection. CoRR abs/2201.00464 (2022) - [i43]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Jingwu Chen, Zhi-Ping Shi, Wenjuan Wu, Qing He:
Multi-Representation Adaptation Network for Cross-domain Image Classification. CoRR abs/2201.01002 (2022) - [i42]Wang Lu, Jindong Wang, Yiqiang Chen, Sinno Jialin Pan, Chunyu Hu, Xin Qin:
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition. CoRR abs/2206.06629 (2022) - [i41]Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie:
MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare. CoRR abs/2206.08516 (2022) - [i40]Han Zhu, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan:
Decoupled Federated Learning for ASR with Non-IID Data. CoRR abs/2206.09102 (2022) - [i39]Han Zhu, Gaofeng Cheng, Jindong Wang, Wenxin Hou, Pengyuan Zhang, Yonghong Yan:
Boosting Cross-Domain Speech Recognition with Self-Supervision. CoRR abs/2206.09783 (2022) - [i38]Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. CoRR abs/2206.12808 (2022) - [i37]Xin Qin, Jindong Wang, Yiqiang Chen, Wang Lu, Xinlong Jiang:
Domain Generalization for Activity Recognition via Adaptive Feature Fusion. CoRR abs/2207.11221 (2022) - [i36]Wang Lu, Jindong Wang, Haoliang Li, Yiqiang Chen, Xing Xie:
Domain-invariant Feature Exploration for Domain Generalization. CoRR abs/2207.12020 (2022) - [i35]Yivan Zhang, Jindong Wang, Xing Xie, Masashi Sugiyama:
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift. CoRR abs/2208.02011 (2022) - [i34]Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang:
USB: A Unified Semi-supervised Learning Benchmark. CoRR abs/2208.07204 (2022) - [i33]Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides:
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets. CoRR abs/2208.07463 (2022) - [i32]Yidong Wang, Hao Wu, Ao Liu, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki, Manabu Okumura, Yue Zhang:
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction. CoRR abs/2208.08280 (2022) - [i31]Yifan Zhang, Jindong Wang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, Xing Xie:
Domain-Specific Risk Minimization. CoRR abs/2208.08661 (2022) - [i30]Wang Lu, Jindong Wang, Yidong Wang, Kan Ren, Yiqiang Chen, Xing Xie:
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. CoRR abs/2209.00652 (2022) - [i29]Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xing Xie:
Out-of-Distribution Representation Learning for Time Series Classification. CoRR abs/2209.07027 (2022) - [i28]Wang Lu, Jindong Wang, Han Yu, Lei Huang, Xiang Zhang, Yiqiang Chen, Xing Xie:
FIXED: Frustratingly Easy Domain Generalization with Mixup. CoRR abs/2211.05228 (2022) - [i27]Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, Jindong Wang, Xing Xie, Yue Zhang:
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective. CoRR abs/2211.08073 (2022) - 2021
- [j11]Wang Lu, Yiqiang Chen, Jindong Wang, Xin Qin:
Cross-domain activity recognition via substructural optimal transport. Neurocomputing 454: 65-75 (2021) - [j10]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1713-1722 (2021) - [c21]Yuntao Du, Jindong Wang, Wenjie Feng, Sinno Jialin Pan, Tao Qin, Renjun Xu, Chongjun Wang:
AdaRNN: Adaptive Learning and Forecasting of Time Series. CIKM 2021: 402-411 - [c20]Linghui Meng, Jin Xu, Xu Tan, Jindong Wang, Tao Qin, Bo Xu:
MixSpeech: Data Augmentation for Low-Resource Automatic Speech Recognition. ICASSP 2021: 7008-7012 - [c19]Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin:
Generalizing to Unseen Domains: A Survey on Domain Generalization. IJCAI 2021: 4627-4635 - [c18]Wenxin Hou, Jindong Wang, Xu Tan, Tao Qin, Takahiro Shinozaki:
Cross-Domain Speech Recognition with Unsupervised Character-Level Distribution Matching. Interspeech 2021: 3425-3429 - [c17]Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu:
Learning Causal Semantic Representation for Out-of-Distribution Prediction. NeurIPS 2021: 6155-6170 - [c16]Bowen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang, Manabu Okumura, Takahiro Shinozaki:
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling. NeurIPS 2021: 18408-18419 - [i26]Wang Lu, Yiqiang Chen, Jindong Wang, Xin Qin:
Cross-domain Activity Recognition via Substructural Optimal Transport. CoRR abs/2102.03353 (2021) - [i25]Linghui Meng, Jin Xu, Xu Tan, Jindong Wang, Tao Qin, Bo Xu:
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition. CoRR abs/2102.12664 (2021) - [i24]Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin:
Generalizing to Unseen Domains: A Survey on Domain Generalization. CoRR abs/2103.03097 (2021) - [i23]Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu:
Learning Invariant Representations across Domains and Tasks. CoRR abs/2103.05114 (2021) - [i22]Wenxin Hou, Jindong Wang, Xu Tan, Tao Qin, Takahiro Shinozaki:
Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching. CoRR abs/2104.07491 (2021) - [i21]Wenxin Hou, Han Zhu, Yidong Wang, Jindong Wang, Tao Qin, Renjun Xu, Takahiro Shinozaki:
Exploiting Adapters for Cross-lingual Low-resource Speech Recognition. CoRR abs/2105.11905 (2021) - [i20]Yiqiang Chen, Wang Lu, Jindong Wang, Xin Qin:
FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare. CoRR abs/2106.01009 (2021) - [i19]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. CoRR abs/2106.09388 (2021) - [i18]Yuxin Zhang, Yiqiang Chen, Jindong Wang, Zhiwen Pan:
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals. CoRR abs/2107.12626 (2021) - [i17]Yuntao Du, Jindong Wang, Wenjie Feng, Sinno Jialin Pan, Tao Qin, Renjun Xu, Chongjun Wang:
AdaRNN: Adaptive Learning and Forecasting of Time Series. CoRR abs/2108.04443 (2021) - [i16]Han Zhu, Li Wang, Ying Hou, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan:
Wav2vec-S: Semi-Supervised Pre-Training for Speech Recognition. CoRR abs/2110.04484 (2021) - [i15]Bowen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang, Manabu Okumura, Takahiro Shinozaki:
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling. CoRR abs/2110.08263 (2021) - [i14]Yiqiang Chen, Wang Lu, Jindong Wang, Xin Qin, Tao Qin:
Federated Learning with Adaptive Batchnorm for Personalized Healthcare. CoRR abs/2112.00734 (2021) - [i13]Yidong Wang, Bowen Zhang, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki:
Margin Calibration for Long-Tailed Visual Recognition. CoRR abs/2112.07225 (2021) - 2020
- [j9]Yiqiang Chen, Xin Qin, Jindong Wang, Chaohui Yu, Wen Gao:
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. IEEE Intell. Syst. 35(4): 83-93 (2020) - [j8]Jindong Wang, Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, Qiang Yang:
Transfer Learning with Dynamic Distribution Adaptation. ACM Trans. Intell. Syst. Technol. 11(1): 6:1-6:25 (2020) - [c15]Renjun Xu, Pelen Liu, Liyan Wang, Chao Chen, Jindong Wang:
Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation. CVPR 2020: 4393-4402 - [c14]Renjun Xu, Pelen Liu, Yin Zhang, Fang Cai, Jindong Wang, Shuoying Liang, Heting Ying, Jianwei Yin:
Joint Partial Optimal Transport for Open Set Domain Adaptation. IJCAI 2020: 2540-2546 - [i12]Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, Tie-Yan Liu:
Learning to Match Distributions for Domain Adaptation. CoRR abs/2007.10791 (2020) - [i11]Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu:
Learning Causal Semantic Representation for Out-of-Distribution Prediction. CoRR abs/2011.01681 (2020)
2010 – 2019
- 2019
- [j7]Xin Qin, Yiqiang Chen, Jindong Wang, Chaohui Yu:
Cross-Dataset Activity Recognition via Adaptive Spatial-Temporal Transfer Learning. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(4): 148:1-148:25 (2019) - [j6]Chaohui Yu, Jindong Wang, Yiqiang Chen, Xin Qin:
Transfer channel pruning for compressing deep domain adaptation models. Int. J. Mach. Learn. Cybern. 10(11): 3129-3144 (2019) - [j5]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Jingwu Chen, Zhiping Shi, Wenjuan Wu, Qing He:
Multi-representation adaptation network for cross-domain image classification. Neural Networks 119: 214-221 (2019) - [j4]Yiqiang Chen, Jindong Wang, Meiyu Huang, Han Yu:
Cross-position activity recognition with stratified transfer learning. Pervasive Mob. Comput. 57: 1-13 (2019) - [j3]Jindong Wang, Yiqiang Chen, Shuji Hao, Xiaohui Peng, Lisha Hu:
Deep learning for sensor-based activity recognition: A survey. Pattern Recognit. Lett. 119: 3-11 (2019) - [c13]Chaohui Yu, Jindong Wang, Yiqiang Chen, Meiyu Huang:
Transfer Learning with Dynamic Adversarial Adaptation Network. ICDM 2019: 778-786 - [c12]Jindong Wang, Yiqiang Chen, Han Yu, Meiyu Huang, Qiang Yang:
Easy Transfer Learning By Exploiting Intra-Domain Structures. ICME 2019: 1210-1215 - [c11]Chaohui Yu, Jindong Wang, Yiqiang Chen, Zijing Wu:
Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning. IJCNN 2019: 1-8 - [c10]Chaohui Yu, Jindong Wang, Yiqiang Chen, Zijing Wu:
Transfer Channel Pruning for Compressing Deep Domain Adaptation Models. PAKDD (Workshops) 2019: 257-273 - [c9]Chaohui Yu, Xin Qin, Yiqiang Chen, Jindong Wang, Chenchen Fan:
DrowsyDet: A Mobile Application for Real-time Driver Drowsiness Detection. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2019: 425-432 - [i10]Jindong Wang, Yiqiang Chen, Han Yu, Meiyu Huang, Qiang Yang:
Easy Transfer Learning By Exploiting Intra-domain Structures. CoRR abs/1904.01376 (2019) - [i9]Chaohui Yu, Jindong Wang, Yiqiang Chen, Zijing Wu:
Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning. CoRR abs/1904.02654 (2019) - [i8]Yiqiang Chen, Jindong Wang, Chaohui Yu, Wen Gao, Xin Qin:
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. CoRR abs/1907.09173 (2019) - [i7]Chaohui Yu, Jindong Wang, Yiqiang Chen, Meiyu Huang:
Transfer Learning with Dynamic Adversarial Adaptation Network. CoRR abs/1909.08184 (2019) - [i6]Jindong Wang, Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, Qiang Yang:
Transfer Learning with Dynamic Distribution Adaptation. CoRR abs/1909.08531 (2019) - 2018
- [j2]Lisha Hu, Yiqiang Chen, Jindong Wang, Chunyu Hu, Xinlong Jiang:
OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition. Int. J. Mach. Learn. Cybern. 9(9): 1577-1590 (2018) - [c8]Jindong Wang, Vincent W. Zheng, Yiqiang Chen, Meiyu Huang:
Deep Transfer Learning for Cross-domain Activity Recognition. ICCSE 2018: 16:1-16:8 - [c7]Jindong Wang, Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, Philip S. Yu:
Visual Domain Adaptation with Manifold Embedded Distribution Alignment. ACM Multimedia 2018: 402-410 - [c6]Jindong Wang, Yiqiang Chen, Lisha Hu, Xiaohui Peng, Philip S. Yu:
Stratified Transfer Learning for Cross-domain Activity Recognition. PerCom 2018: 1-10 - [i5]Jindong Wang, Yiqiang Chen, Lisha Hu, Xiaohui Peng, Philip S. Yu:
Stratified Transfer Learning for Cross-domain Activity Recognition. CoRR abs/1801.00820 (2018) - [i4]Yiqiang Chen, Jindong Wang, Meiyu Huang, Han Yu:
Cross-position Activity Recognition with Stratified Transfer Learning. CoRR abs/1806.09776 (2018) - [i3]Jindong Wang, Yiqiang Chen, Shuji Hao, Wenjie Feng, Zhiqi Shen:
Balanced Distribution Adaptation for Transfer Learning. CoRR abs/1807.00516 (2018) - [i2]Jindong Wang, Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, Philip S. Yu:
Visual Domain Adaptation with Manifold Embedded Distribution Alignment. CoRR abs/1807.07258 (2018) - 2017
- [j1]Faizan Ahmad, Yiqiang Chen, Lisha Hu, Shuangquan Wang, Jindong Wang, Zhenyu Chen, Xinlong Jiang, Jianfei Shen:
BrainStorm: a psychosocial game suite design for non-invasive cross-generational cognitive capabilities data collection. J. Exp. Theor. Artif. Intell. 29(6): 1311-1323 (2017) - [c5]Jindong Wang, Yiqiang Chen, Shuji Hao, Wenjie Feng, Zhiqi Shen:
Balanced Distribution Adaptation for Transfer Learning. ICDM 2017: 1129-1134 - [c4]Xiaohai Li, Yiqiang Chen, Zhongdong Wu, Xiaohui Peng, Jindong Wang, Lisha Hu, Diancun Yu:
Weak multipath effect identification for indoor distance estimation. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017: 1-8 - [i1]Jindong Wang, Yiqiang Chen, Shuji Hao, Xiaohui Peng, Lisha Hu:
Deep Learning for Sensor-based Activity Recognition: A Survey. CoRR abs/1707.03502 (2017) - 2016
- [c3]Yiqiang Chen, Yang Gu, Xinlong Jiang, Jindong Wang:
OCEAN: a new opportunistic computing model for wearable activity recognition. UbiComp Adjunct 2016: 33-36 - [c2]Faizan Ahmad, Yiqiang Chen, Shuangquan Wang, Zhenyu Chen, Jianfei Shen, Lisha Hu, Jindong Wang:
A Study of Players' Experiences During Brain Games Play. PRICAI 2016: 3-15 - [c1]Lisha Hu, Yiqiang Chen, Shuangquan Wang, Jindong Wang, Jianfei Shen, Xinlong Jiang, Zhiqi Shen:
Less Annotation on Personalized Activity Recognition Using Context Data. UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld 2016: 327-332
Coauthor Index
[j28] [j26] [j24] [j21] [j20] [j19] [j17] [j16] [c37] [c35] [i65] [i61] [i54] [j15] [j12] [c27] [c22] [i44] [i42] [i41] [i37] [i36] [i30] [i29] [i28] [j11] [i26] [i20] [i18] [i14] [j9] [j8] [i12] [j7] [j6] [j4] [j3] [c13] [c12] [c11] [c10] [c9] [i10] [i9] [i8] [i7] [i6] [j2] [c8] [c7] [c6] [i5] [i4] [i3] [i2] [j1] [c5] [c4] [i1] [c3] [c2] [c1]
[i114] [i113] [j31] [j30] [j29] [j28] [j25] [j24] [c70] [c66] [c64] [c63] [c62] [c61] [c59] [c58] [c57] [c54] [c53] [c51] [c49] [c47] [c46] [c45] [c44] [i112] [i110] [i109] [i107] [i106] [i104] [i103] [i100] [i99] [i95] [i91] [i74] [j23] [c42] [c41] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c30] [i73] [i72] [i71] [i70] [i69] [i66] [i65] [i64] [i63] [i62] [i61] [i60] [i59] [i58] [i57] [i56] [i55] [i54] [i53] [i51] [i47] [i46] [i45] [j12] [c23] [i41] [i36] [i35] [i34] [i31] [i30] [i29] [i28] [i27]
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