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2020 – today
- 2024
[j5]Zifan Zhang, Yuchen Liu, Zhiyuan Peng, Mingzhe Chen, Dongkuan Xu, Shuguang Cui:
Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks. IEEE J. Sel. Areas Commun. 42(11): 3306-3320 (2024)- [j4]Dongsheng Luo
, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang:
Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5245-5259 (2024) - [j3]Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick:
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. Trans. Mach. Learn. Res. 2024 (2024) - [c46]Zhengdong Zhang, Zihan Dong, Yang Shi, Thomas W. Price, Noboru Matsuda, Dongkuan Xu:
Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming. AAAI 2024: 23250-23258 - [c45]Ziqing Wang, Qidong Zhao, Jinku Cui, Xu Liu, Dongkuan Xu:
Autost: Training-Free Neural Architecture Search For Spiking Transformers. ICASSP 2024: 3455-3459 - [c44]Yi Wang, Qidong Zhao, Dongkuan Xu, Xu Liu:
Purpose Enhanced Reasoning through Iterative Prompting: Uncover Latent Robustness of ChatGPT on Code Comprehension. IJCAI 2024: 6513-6521 - [c43]Xinpeng Wang, Shitong Duan, Xiaoyuan Yi, Jing Yao, Shanlin Zhou, Zhihua Wei, Peng Zhang, Dongkuan Xu, Maosong Sun, Xing Xie:
On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models. IJCAI 2024: 8308-8316 - [c42]Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu:
RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2024: 6749-6750 - [c41]Xuanhao Luo, Zhizhen Li, Zhiyuan Peng, Dongkuan Xu, Yuchen Liu:
RM-Gen: Conditional Diffusion Model-Based Radio Map Generation for Wireless Networks. IFIP Networking 2024: 543-548 - [i37]Xukun Liu, Zhiyuan Peng, Xiaoyuan Yi, Xing Xie, Lirong Xiang, Yuchen Liu, Dongkuan Xu:
ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph. CoRR abs/2403.00839 (2024) - [i36]Xinpeng Wang, Shitong Duan, Xiaoyuan Yi, Jing Yao, Shanlin Zhou, Zhihua Wei, Peng Zhang, Dongkuan Xu, Maosong Sun, Xing Xie:
On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models. CoRR abs/2403.04204 (2024) - [i35]Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick:
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. CoRR abs/2403.20047 (2024) - [i34]Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu:
Improving Logits-based Detector without Logits from Black-box LLMs. CoRR abs/2406.05232 (2024) - [i33]Zifan Zhang, Yuchen Liu, Zhiyuan Peng, Mingzhe Chen, Dongkuan Xu, Shuguang Cui:
Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks. CoRR abs/2407.00286 (2024) - [i32]Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu:
Adaptive Draft-Verification for Efficient Large Language Model Decoding. CoRR abs/2407.12021 (2024) - 2023
- [j2]Yingjie Tian, Weizhi Gao, Qin Zhang, Pu Sun, Dongkuan Xu:
Improving long-tailed classification by disentangled variance transfer. Internet Things 21: 100687 (2023) - [c40]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. AAAI 2023: 4534-4542 - [c39]Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou, Sergii Skakun:
Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics. AAAI 2023: 14575-14583 - [c38]Qin Zhang, Shangsi Chen, Dongkuan Xu, Qingqing Cao, Xiaojun Chen, Trevor Cohn, Meng Fang:
A Survey for Efficient Open Domain Question Answering. ACL (1) 2023: 14447-14465 - [c37]Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang:
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. AISTATS 2023: 7288-7310 - [c36]Chengyuan Liu, Divyang Doshi, Muskaan Bhargava, Ruixuan Shang, Jialin Cui, Dongkuan Xu, Edward F. Gehringer:
Labels are not necessary: Assessing peer-review helpfulness using domain adaptation based on self-training. BEA@ACL 2023: 173-183 - [c35]Shuya Li, Hao Mei, Jianwei Li, Hua Wei, Dongkuan Xu:
Toward Efficient Traffic Signal Control: Smaller Network Can Do More. CDC 2023: 8069-8074 - [c34]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CVPR 2023: 10781-10791 - [c33]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CVPR 2023: 11950-11959 - [c32]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC 2023: 1-6 - [c31]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC 2023: 1-6 - [c30]Binfeng Xu, Xukun Liu, Hua Shen, Zeyu Han, Yuhan Li, Murong Yue, Zhiyuan Peng, Yuchen Liu, Ziyu Yao, Dongkuan Xu:
Gentopia.AI: A Collaborative Platform for Tool-Augmented LLMs. EMNLP (Demos) 2023: 237-245 - [c29]Jianwei Li, Qi Lei, Wei Cheng, Dongkuan Xu:
Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models. EMNLP 2023: 1229-1247 - [c28]Jianwei Li, Weizhi Gao, Qi Lei, Dongkuan Xu:
Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection. EMNLP (Findings) 2023: 11407-11423 - [c27]Yuchen Liu, Mingzhe Chen, Dongkuan Xu, Zhaohui Yang, Shangqing Zhao:
E-App: Adaptive mmWave Access Point Planning with Environmental Awareness in Wireless LANs. ICCCN 2023: 1-10 - [c26]Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang:
Rethinking Data Distillation: Do Not Overlook Calibration. ICCV 2023: 4912-4922 - [c25]Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick:
Calibrating the Rigged Lottery: Making All Tickets Reliable. ICLR 2023 - [c24]Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou:
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. KDD 2023: 2629-2638 - [c23]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c22]Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma:
Towards Personalized Federated Learning via Heterogeneous Model Reassembly. NeurIPS 2023 - [i31]Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick:
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction. CoRR abs/2301.03573 (2023) - [i30]Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick:
Calibrating the Rigged Lottery: Making All Tickets Reliable. CoRR abs/2302.09369 (2023) - [i29]Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang:
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. CoRR abs/2302.13929 (2023) - [i28]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. CoRR abs/2303.11911 (2023) - [i27]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR abs/2304.12214 (2023) - [i26]Binfeng Xu, Zhiyuan Peng, Bowen Lei, Subhabrata Mukherjee, Yuchen Liu, Dongkuan Xu:
ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models. CoRR abs/2305.18323 (2023) - [i25]Ziqing Wang, Qidong Zhao, Jinku Cui, Xu Liu, Dongkuan Xu:
AutoST: Training-free Neural Architecture Search for Spiking Transformers. CoRR abs/2307.00293 (2023) - [i24]Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou:
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. CoRR abs/2307.09858 (2023) - [i23]Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang, Ruqi Zhang, Yiqun Xie, Dongkuan Xu:
Rethinking Data Distillation: Do Not Overlook Calibration. CoRR abs/2307.12463 (2023) - [i22]Binfeng Xu, Xukun Liu, Hua Shen, Zeyu Han, Yuhan Li, Murong Yue, Zhiyuan Peng, Yuchen Liu, Ziyu Yao, Dongkuan Xu:
Gentopia: A Collaborative Platform for Tool-Augmented LLMs. CoRR abs/2308.04030 (2023) - [i21]Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma:
Towards Personalized Federated Learning via Heterogeneous Model Reassembly. CoRR abs/2308.08643 (2023) - [i20]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. CoRR abs/2309.17074 (2023) - [i19]Jianwei Li, Weizhi Gao, Qi Lei, Dongkuan Xu:
Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection. CoRR abs/2310.13183 (2023) - [i18]Jianwei Li, Qi Lei, Wei Cheng, Dongkuan Xu:
Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models. CoRR abs/2310.13191 (2023) - [i17]Jianwei Li, Tianchi Zhang, Ian En-Hsu Yen, Dongkuan Xu:
FP8-BERT: Post-Training Quantization for Transformer. CoRR abs/2312.05725 (2023) - [i16]Zhengdong Zhang, Zihan Dong, Yang Shi, Noboru Matsuda, Thomas W. Price, Dongkuan Xu:
Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming. CoRR abs/2312.11567 (2023) - 2022
- [c21]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 2022: 190-200 - [c20]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED 2022: 1-6 - [c19]Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao:
Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. NeurIPS 2022 - [i15]Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao:
AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. CoRR abs/2201.12507 (2022) - [i14]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR abs/2206.10461 (2022) - [i13]Ian En-Hsu Yen, Zhibin Xiao, Dongkuan Xu:
S4: a High-sparsity, High-performance AI Accelerator. CoRR abs/2207.08006 (2022) - [i12]Qin Zhang, Shangsi Chen, Dongkuan Xu, Qingqing Cao, Xiaojun Chen, Trevor Cohn, Meng Fang:
A Survey for Efficient Open Domain Question Answering. CoRR abs/2211.07886 (2022) - [i11]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CoRR abs/2211.11152 (2022) - [i10]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR abs/2211.16667 (2022) - [i9]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CoRR abs/2212.06152 (2022) - 2021
- [c18]Hua Wei, Dongkuan Xu, Junjie Liang, Zhenhui Li:
How Do We Move: Modeling Human Movement with System Dynamics. AAAI 2021: 4445-4452 - [c17]Dongkuan Xu, Junjie Liang, Wei Cheng, Hua Wei, Haifeng Chen, Xiang Zhang:
Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling. AAAI 2021: 4546-4554 - [c16]Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar:
Longitudinal Deep Kernel Gaussian Process Regression. AAAI 2021: 8556-8564 - [c15]Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang:
Multi-Task Recurrent Modular Networks. AAAI 2021: 10496-10504 - [c14]Xin Dong, Yaxin Zhu, Zuohui Fu, Dongkuan Xu, Gerard de Melo:
Data Augmentation with Adversarial Training for Cross-Lingual NLI. ACL/IJCNLP (1) 2021: 5158-5167 - [c13]Dongkuan Xu, Ian En-Hsu Yen, Jinxi Zhao, Zhibin Xiao:
Rethinking Network Pruning - under the Pre-train and Fine-tune Paradigm. NAACL-HLT 2021: 2376-2382 - [c12]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang:
InfoGCL: Information-Aware Graph Contrastive Learning. NeurIPS 2021: 30414-30425 - [c11]Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang:
Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection. SDM 2021: 91-99 - [i8]Dongkuan Xu, Ian En-Hsu Yen, Jinxi Zhao, Zhibin Xiao:
Rethinking Network Pruning - under the Pre-train and Fine-tune Paradigm. CoRR abs/2104.08682 (2021) - [i7]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR abs/2110.08190 (2021) - [i6]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang:
InfoGCL: Information-Aware Graph Contrastive Learning. CoRR abs/2110.15438 (2021) - 2020
- [c10]Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang:
Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. AAAI 2020: 1395-1402 - [c9]Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar:
LMLFM: Longitudinal Multi-Level Factorization Machine. AAAI 2020: 4811-4818 - [c8]Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang:
Parameterized Explainer for Graph Neural Network. NeurIPS 2020 - [c7]Xin Dong, Yaxin Zhu, Yupeng Zhang, Zuohui Fu, Dongkuan Xu, Sen Yang, Gerard de Melo:
Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification. SIGIR 2020: 1541-1544 - [i5]Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar:
Longitudinal Deep Kernel Gaussian Process Regression. CoRR abs/2005.11770 (2020) - [i4]Xin Dong, Yaxin Zhu, Yupeng Zhang, Zuohui Fu, Dongkuan Xu, Sen Yang, Gerard de Melo:
Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification. CoRR abs/2007.15072 (2020) - [i3]Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang:
Parameterized Explainer for Graph Neural Network. CoRR abs/2011.04573 (2020)
2010 – 2019
- 2019
- [c6]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang:
Adaptive Neural Network for Node Classification in Dynamic Networks. ICDM 2019: 1402-1407 - [c5]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang:
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs. IJCAI 2019: 3947-3953 - [c4]Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Deep Co-Clustering. SDM 2019: 414-422 - [i2]Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar:
LMLFM: Longitudinal Multi-Level Factorization Machine. CoRR abs/1911.04062 (2019) - 2018
- [c3]Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang:
Co-Regularized Deep Multi-Network Embedding. WWW 2018: 469-478 - 2017
- [j1]Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian, Xingquan Zhu, Xindong Wu:
SALE: Self-adaptive LSH encoding for multi-instance learning. Pattern Recognit. 71: 460-482 (2017) - [c2]Dewei Li, Dongkuan Xu, Jingjing Tang, Yingjie Tian:
Metric learning for multi-instance classification with collapsed bags. IJCNN 2017: 372-379 - 2016
- [i1]Dongkuan Xu, Jia Wu, Wei Zhang, Yingjie Tian:
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning. CoRR abs/1612.03550 (2016) - 2014
- [c1]Dongkuan Xu, Yi Zhang, Cheng Cheng, Wei Xu, Likuan Zhang:
A Neural Network-Based Ensemble Prediction Using PMRS and ECM. HICSS 2014: 1335-1343
Coauthor Index
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