Dongkuan Xu

According to our database, Dongkuan Xu authored at least 57 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick

CoRR, 2024

On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models.

Xinpeng Wang, Shitong Duan, Xiaoyuan Yi, Jing Yao, Shanlin Zhou, Zhihua Wei, Peng Zhang, Dongkuan Xu, Maosong Sun, Xing Xie

CoRR, 2024

ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph.

Xukun Liu, Zhiyuan Peng, Xiaoyuan Yi, Xing Xie, Lirong Xiang, Yuchen Liu, Dongkuan Xu

CoRR, 2024

Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming.

Zhengdong Zhang, Zihan Dong, Yang Shi, Thomas W. Price, Noboru Matsuda, Dongkuan Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Improving long-tailed classification by disentangled variance transfer.

Yingjie Tian, Weizhi Gao, Qin Zhang, Pu Sun, Dongkuan Xu

Internet Things, April, 2023

FP8-BERT: Post-Training Quantization for Transformer.

Jianwei Li, Tianchi Zhang, Ian En-Hsu Yen, Dongkuan Xu

CoRR, 2023

DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation.

Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu

CoRR, 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly.

Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma

CoRR, 2023

Gentopia: A Collaborative Platform for Tool-Augmented LLMs.

Binfeng Xu, Xukun Liu, Hua Shen, Zeyu Han, Yuhan Li, Murong Yue, Zhiyuan Peng, Yuchen Liu, Ziyu Yao, Dongkuan Xu

CoRR, 2023

AutoST: Training-free Neural Architecture Search for Spiking Transformers.

Ziqing Wang, Qidong Zhao, Jinku Cui, Xu Liu, Dongkuan Xu

CoRR, 2023

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models.

Binfeng Xu, Zhiyuan Peng, Bowen Lei, Subhabrata Mukherjee, Yuchen Liu, Dongkuan Xu

CoRR, 2023

Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick

CoRR, 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly.

Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan Xu, Fenglong Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery.

Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration.

Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Calibrating the Rigged Lottery: Making All Tickets Reliable.

Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Rethinking Data Distillation: Do Not Overlook Calibration.

Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

E-App: Adaptive mmWave Access Point Planning with Environmental Awareness in Wireless LANs.

Yuchen Liu, Mingzhe Chen, Dongkuan Xu, Zhaohui Yang, Shangqing Zhao

Proceedings of the 32nd International Conference on Computer Communications and Networks, 2023

Gentopia.AI: A Collaborative Platform for Tool-Augmented LLMs.

Binfeng Xu, Xukun Liu, Hua Shen, Zeyu Han, Yuhan Li, Murong Yue, Zhiyuan Peng, Yuchen Liu, Ziyu Yao, Dongkuan Xu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models.

Jianwei Li, Qi Lei, Wei Cheng, Dongkuan Xu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection.

Jianwei Li, Weizhi Gao, Qi Lei, Dongkuan Xu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off.

Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration.

Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Accelerating Dataset Distillation via Model Augmentation.

Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model.

Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Toward Efficient Traffic Signal Control: Smaller Network Can Do More.

Shuya Li, Hao Mei, Jianwei Li, Hua Wei, Dongkuan Xu

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Labels are not necessary: Assessing peer-review helpfulness using domain adaptation based on self-training.

Chengyuan Liu, Divyang Doshi, Muskaan Bhargava, Ruixuan Shang, Jialin Cui, Dongkuan Xu, Edward F. Gehringer

Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications, 2023

Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation.

Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

A Survey for Efficient Open Domain Question Answering.

Qin Zhang, Shangsi Chen, Dongkuan Xu, Qingqing Cao, Xiaojun Chen, Trevor Cohn, Meng Fang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics.

Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou, Sergii Skakun

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Time Series Contrastive Learning with Information-Aware Augmentations.

Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

S4: a High-sparsity, High-performance AI Accelerator.

Ian En-Hsu Yen, Zhibin Xiao, Dongkuan Xu

CoRR, 2022

AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models.

Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao

CoRR, 2022

Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models.

Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

An Automatic and Efficient BERT Pruning for Edge AI Systems.

Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

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

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding

CoRR, 2021

Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection.

Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

InfoGCL: Information-Aware Graph Contrastive Learning.

Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rethinking Network Pruning - under the Pre-train and Fine-tune Paradigm.

Dongkuan Xu, Ian En-Hsu Yen, Jinxi Zhao, Zhibin Xiao

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Data Augmentation with Adversarial Training for Cross-Lingual NLI.

Xin Dong, Yaxin Zhu, Zuohui Fu, Dongkuan Xu, Gerard de Melo

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling.

Dongkuan Xu, Junjie Liang, Wei Cheng, Hua Wei, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Multi-Task Recurrent Modular Networks.

Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Longitudinal Deep Kernel Gaussian Process Regression.

Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

How Do We Move: Modeling Human Movement with System Dynamics.

Hua Wei, Dongkuan Xu, Junjie Liang, Zhenhui Li

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification.

Xin Dong, Yaxin Zhu, Yupeng Zhang, Zuohui Fu, Dongkuan Xu, Sen Yang, Gerard de Melo

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Parameterized Explainer for Graph Neural Network.

Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series.

Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

LMLFM: Longitudinal Multi-Level Factorization Machine.

Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep Co-Clustering.

Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs.

Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Adaptive Neural Network for Node Classification in Dynamic Networks.

Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

Co-Regularized Deep Multi-Network Embedding.

Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

2017

SALE: Self-adaptive LSH encoding for multi-instance learning.

Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian, Xingquan Zhu, Xindong Wu

Pattern Recognit., 2017

Metric learning for multi-instance classification with collapsed bags.

Dewei Li, Dongkuan Xu, Jingjing Tang, Yingjie Tian

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning.

Dongkuan Xu, Jia Wu, Wei Zhang, Yingjie Tian

CoRR, 2016

2014

A Neural Network-Based Ensemble Prediction Using PMRS and ECM.

Dongkuan Xu, Yi Zhang, Cheng Cheng, Wei Xu, Likuan Zhang

Proceedings of the 47th Hawaii International Conference on System Sciences, 2014