A Neural Network-Based Ensemble Prediction Using PMRS and ECM. - Dongkuan Xu; Yi Zhang; Cheng Cheng; Wei Xu 008; Likuan Zhang (HICSS, 2014)

PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning. - Dongkuan Xu; Jia Wu 001; Wei Zhang 098; Yingjie Tian 001 (CoRR, 2016)

Metric learning for multi-instance classification with collapsed bags. - Dewei Li 002; Dongkuan Xu; Jingjing Tang; Yingjie Tian 001 (IJCNN, 2017)

SALE: Self-adaptive LSH encoding for multi-instance learning. - Dongkuan Xu; Jia Wu 001; Dewei Li 002; Yingjie Tian 001; Xingquan Zhu 001; Xindong Wu 001 (Pattern Recognit., 2017)

Co-Regularized Deep Multi-Network Embedding. - Jingchao Ni; Shiyu Chang; Xiao Liu 039; Wei Cheng 002; Haifeng Chen; Dongkuan Xu; Xiang Zhang 001 (WWW, 2018)

Adaptive Neural Network for Node Classification in Dynamic Networks. - Dongkuan Xu; Wei Cheng 002; Dongsheng Luo; Yameng Gu; Xiao Liu 039; Jingchao Ni; Bo Zong; Haifeng Chen; Xiang Zhang 001 (ICDM, 2019)

Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs. - Dongkuan Xu; Wei Cheng 002; Dongsheng Luo; Xiao Liu 039; Xiang Zhang 001 (IJCAI, 2019)

Deep Co-Clustering. - Dongkuan Xu; Wei Cheng 002; Bo Zong; Jingchao Ni; Dongjin Song; Wenchao Yu; Yuncong Chen; Haifeng Chen; Xiang Zhang 001 (SDM, 2019)

LMLFM: Longitudinal Multi-Level Factorization Machine. - Junjie Liang; Dongkuan Xu; Yiwei Sun; Vasant G. Honavar (AAAI, 2020)

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. - Dongkuan Xu; Wei Cheng 002; Bo Zong; Dongjin Song; Jingchao Ni; Wenchao Yu; Yanchi Liu; Haifeng Chen; Xiang Zhang 001 (AAAI, 2020)

Parameterized Explainer for Graph Neural Network. - Dongsheng Luo; Wei Cheng 002; Dongkuan Xu; Wenchao Yu; Bo Zong; Haifeng Chen; Xiang Zhang 001 (NeurIPS, 2020)

Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification. - Xin Dong 010; Yaxin Zhu; Yupeng Zhang; Zuohui Fu; Dongkuan Xu; Sen Yang 002; Gerard de Melo (SIGIR, 2020)

How Do We Move: Modeling Human Movement with System Dynamics. - Hua Wei 001; Dongkuan Xu; Junjie Liang; Zhenhui Li (AAAI, 2021)

Longitudinal Deep Kernel Gaussian Process Regression. - Junjie Liang; Yanting Wu; Dongkuan Xu; Vasant G. Honavar (AAAI, 2021)

Multi-Task Recurrent Modular Networks. - Dongkuan Xu; Wei Cheng 002; Xin Dong 010; Bo Zong; Wenchao Yu; Jingchao Ni; Dongjin Song; Xuchao Zhang; Haifeng Chen; Xiang Zhang 001 (AAAI, 2021)

Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling. - Dongkuan Xu; Junjie Liang; Wei Cheng 002; Hua Wei 001; Haifeng Chen; Xiang Zhang 001 (AAAI, 2021)

Data Augmentation with Adversarial Training for Cross-Lingual NLI. - Xin Dong 010; Yaxin Zhu; Zuohui Fu; Dongkuan Xu; Gerard de Melo (ACL/IJCNLP (1), 2021)

Rethinking Network Pruning - under the Pre-train and Fine-tune Paradigm. - Dongkuan Xu; Ian En-Hsu Yen; Jinxi Zhao; Zhibin Xiao (NAACL-HLT, 2021)

InfoGCL: Information-Aware Graph Contrastive Learning. - Dongkuan Xu; Wei Cheng 002; Dongsheng Luo; Haifeng Chen; Xiang Zhang 001 (NeurIPS, 2021)

Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection. - Dongkuan Xu; Wei Cheng 002; Jingchao Ni; Dongsheng Luo; Masanao Natsumeda; Dongjin Song; Bo Zong; Haifeng Chen; Xiang Zhang 001 (SDM, 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 004; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

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 004; Mimi Xie; Sanguthevar Rajasekaran; Hang Liu 001; Caiwen Ding (ACL (1), 2022)

An Automatic and Efficient BERT Pruning for Edge AI Systems. - Shaoyi Huang; Ning Liu 007; Yueying Liang; Hongwu Peng; Hongjia Li; Dongkuan Xu; Mimi Xie; Caiwen Ding (ISQED, 2022)

Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. - Dongkuan Xu; Subhabrata Mukherjee; Xiaodong Liu 003; Debadeepta Dey; Wenhui Wang 003; Xiang Zhang 001; Ahmed Hassan Awadallah; Jianfeng Gao 001 (NeurIPS, 2022)

AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. - Dongkuan Xu; Subhabrata Mukherjee; Xiaodong Liu 003; Debadeepta Dey; Wenhui Wang 003; Xiang Zhang 001; Ahmed Hassan Awadallah; Jianfeng Gao 001 (CoRR, 2022)

S4: a High-sparsity, High-performance AI Accelerator. - Ian En-Hsu Yen; Zhibin Xiao; Dongkuan Xu (CoRR, 2022)

Time Series Contrastive Learning with Information-Aware Augmentations. - Dongsheng Luo; Wei Cheng 002; Yingheng Wang; Dongkuan Xu; Jingchao Ni; Wenchao Yu; Xuchao Zhang; Yanchi Liu; Yuncong Chen; Haifeng Chen; Xiang Zhang 001 (AAAI, 2023)

Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics. - Yiqun Xie; Zhili Li; Han Bao 003; Xiaowei Jia; Dongkuan Xu; Xun Zhou 001; Sergii Skakun (AAAI, 2023)

A Survey for Efficient Open Domain Question Answering. - Qin Zhang 011; Shangsi Chen; Dongkuan Xu; Qingqing Cao; Xiaojun Chen 006; Trevor Cohn; Meng Fang (ACL (1), 2023)

Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. - Yue Xiang; Dongyao Zhu; Bowen Lei; Dongkuan Xu; Ruqi Zhang (AISTATS, 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 (BEA@ACL, 2023)

Toward Efficient Traffic Signal Control: Smaller Network Can Do More. - Shuya Li; Hao Mei; Jianwei Li 004; Hua Wei 001; Dongkuan Xu (CDC, 2023)

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. - Shengkun Tang; Yaqing Wang 001; Zhenglun Kong; Tianchi Zhang 004; Yao Li 015; Caiwen Ding; Yanzhi Wang; Yi Liang; Dongkuan Xu (CVPR, 2023)

Accelerating Dataset Distillation via Model Augmentation. - Lei Zhang 197; Jie Zhang 081; Bowen Lei; Subhabrata Mukherjee; Xiang Pan 001; Bo Zhao; Caiwen Ding; Yao Li 015; Dongkuan Xu (CVPR, 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 (DAC, 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 (DAC, 2023)

Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection. - Jianwei Li 004; Weizhi Gao; Qi Lei; Dongkuan Xu (EMNLP (Findings), 2023)

Towards Robust Pruning: An Adaptive Knowledge-Retention Pruning Strategy for Language Models. - Jianwei Li 004; Qi Lei; Wei Cheng 002; Dongkuan Xu (EMNLP, 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 001; Ziyu Yao 002; Dongkuan Xu (EMNLP (Demos), 2023)

E-App: Adaptive mmWave Access Point Planning with Environmental Awareness in Wireless LANs. - Yuchen Liu 001; Mingzhe Chen; Dongkuan Xu; Zhaohui Yang 001; Shangqing Zhao (ICCCN, 2023)

Rethinking Data Distillation: Do Not Overlook Calibration. - Dongyao Zhu; Yanbo Fang; Bowen Lei; Yiqun Xie; Dongkuan Xu; Jie Zhang 081; Ruqi Zhang (ICCV, 2023)

Calibrating the Rigged Lottery: Making All Tickets Reliable. - Bowen Lei; Ruqi Zhang; Dongkuan Xu; Bani K. Mallick (ICLR, 2023)

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. - Longfeng Wu; Bowen Lei; Dongkuan Xu; Dawei Zhou 003 (KDD, 2023)

RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. - Chuxu Zhang; Dongkuan Xu; Mojan Javaheripi; Subhabrata Mukherjee; Lingfei Wu 001; Yinglong Xia; Jundong Li; Meng Jiang 001; Yanzhi Wang (KDD, 2023)

Towards Personalized Federated Learning via Heterogeneous Model Reassembly. - Jiaqi Wang 002; Xingyi Yang; Suhan Cui; Liwei Che; Lingjuan Lyu; Dongkuan Xu; Fenglong Ma (NeurIPS, 2023)

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models. - Binfeng Xu; Zhiyuan Peng; Bowen Lei; Subhabrata Mukherjee; Yuchen Liu 001; Dongkuan Xu (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 001; Ziyu Yao 002; Dongkuan Xu (CoRR, 2023)

DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. - Shengkun Tang; Yaqing Wang 001; Caiwen Ding; Yi Liang; Yao Li 015; Dongkuan Xu (CoRR, 2023)

FP8-BERT: Post-Training Quantization for Transformer. - Jianwei Li 004; Tianchi Zhang 004; Ian En-Hsu Yen; Dongkuan Xu (CoRR, 2023)

Improving long-tailed classification by disentangled variance transfer. - Yingjie Tian 001; Weizhi Gao; Qin Zhang 011; Pu Sun; Dongkuan Xu (Internet Things, 2023)

Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming. - Zhengdong Zhang; Zihan Dong; Yang Shi 004; Thomas W. Price; Noboru Matsuda; Dongkuan Xu (AAAI, 2024)

Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction. - Bowen Lei; Dongkuan Xu; Ruqi Zhang; Shuren He; Bani K. Mallick (CPAL, 2024)

AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. - Shengkun Tang; Yaqing Wang 001; Caiwen Ding; Yi Liang; Yao Li 015; Dongkuan Xu (ECCV (79), 2024)

Empowering Secondary School Teachers: Creating, Executing, and Evaluating a Transformative Professional Development Course on ChatGPT. - Heidi Reichert; Benyamin T. Tabarsi; Zifan Zhang; Cheri Fennell; Indira Bhandari; David Robinson; Madeline Drayton; Catherine Crofton; Matthew Lococo; Dongkuan Xu; Tiffany Barnes (FIE, 2024)

Autost: Training-Free Neural Architecture Search For Spiking Transformers. - Ziqing Wang; Qidong Zhao; Jinku Cui; Xu Liu 001; Dongkuan Xu (ICASSP, 2024)

On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models. - Xinpeng Wang 001; Shitong Duan; Xiaoyuan Yi; Jing Yao; Shanlin Zhou; Zhihua Wei 001; Peng Zhang 060; Dongkuan Xu; Maosong Sun 001; Xing Xie 001 (IJCAI, 2024)

Purpose Enhanced Reasoning through Iterative Prompting: Uncover Latent Robustness of ChatGPT on Code Comprehension. - Yi Wang; Qidong Zhao; Dongkuan Xu; Xu Liu 001 (IJCAI, 2024)

Revolutionizing Wireless Modeling and Simulation with Network-Oriented LLMs. - Jiewen Liu; Zhiyuan Peng; Dongkuan Xu; Yuchen Liu 001 (IPCCC, 2024)

RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. - Chuxu Zhang; Dongkuan Xu; Kaize Ding; Jundong Li; Mojan Javaheripi; Subhabrata Mukherjee; Nitesh V. Chawla; Huan Liu 001 (KDD, 2024)

RM-Gen: Conditional Diffusion Model-Based Radio Map Generation for Wireless Networks. - Xuanhao Luo; Zhizhen Li; Zhiyuan Peng; Dongkuan Xu; Yuchen Liu 001 (IFIP Networking, 2024)

DALD: Improving Logits-based Detector without Logits from Black-box LLMs. - Cong Zeng; Shengkun Tang; Xianjun Yang; Yuanzhou Chen; Yiyou Sun; Zhiqiang Xu; Yao Li 015; Haifeng Chen; Wei Cheng 002; Dongkuan Xu (NeurIPS, 2024)

ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph. - Xukun Liu; Zhiyuan Peng; Xiaoyuan Yi; Xing Xie 001; Lirong Xiang; Yuchen Liu 001; Dongkuan Xu (CoRR, 2024)

Improving Logits-based Detector without Logits from Black-box LLMs. - Cong Zeng; Shengkun Tang; Xianjun Yang; Yuanzhou Chen; Yiyou Sun; Zhiqiang Xu; Yao Li 015; Haifeng Chen; Wei Cheng 002; Dongkuan Xu (CoRR, 2024)

Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for Precise Causal Discovery. - ChengAo Shen; Zhengzhang Chen; Dongsheng Luo; Dongkuan Xu; Haifeng Chen; Jingchao Ni (CoRR, 2024)

Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. - Bowen Lei; Dongkuan Xu; Ruqi Zhang; Bani K. Mallick (Trans. Mach. Learn. Res., 2024)

Towards Inductive and Efficient Explanations for Graph Neural Networks. - Dongsheng Luo; Tianxiang Zhao 001; Wei Cheng 002; Dongkuan Xu; Feng Han; Wenchao Yu; Xiao Liu 039; Haifeng Chen; Xiang Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks. - Zifan Zhang; Yuchen Liu 001; Zhiyuan Peng; Mingzhe Chen; Dongkuan Xu; Shuguang Cui (IEEE J. Sel. Areas Commun., 2024)

EQ-ViT: Algorithm-Hardware Co-Design for End-to-End Acceleration of Real-Time Vision Transformer Inference on Versal ACAP Architecture. - Peiyan Dong; Jinming Zhuang; Zhuoping Yang; Shixin Ji; Yanyu Li; Dongkuan Xu; Heng Huang; Jingtong Hu; Alex K. Jones; Yiyu Shi 001; Yanzhi Wang; Peipei Zhou 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Adaptive Draft-Verification for Efficient Large Language Model Decoding. - Xukun Liu; Bowen Lei; Ruqi Zhang; Dongkuan Xu (AAAI, 2025)

MerryQuery: A Trustworthy LLM-Powered Tool Providing Personalized Support for Educators and Students. - Benyamin T. Tabarsi; Aditya Basarkar; Xukun Liu; Dongkuan Xu; Tiffany Barnes (AAAI, 2025)

DyESP: Accelerating Hyperparameter-Architecture Search via Dynamic Exploration and Space Pruning. - Xukun Liu; Haoze Lv; Fenglong Ma; Chi Wang; Dongkuan Xu (AAAI Spring Symposia, 2025)

Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery. - ChengAo Shen; Zhengzhang Chen; Dongsheng Luo; Dongkuan Xu; Haifeng Chen; Jingchao Ni (ACL (Findings), 2025)

IOAgent: Democratizing Trustworthy HPC I/O Performance Diagnosis Capability via LLMs. - Chris Egersdoerfer; Arnav Sareen; Jean Luca Bez; Suren Byna; Dongkuan Xu; Dong Dai 001 (IPDPS, 2025)

Resource-Efficient Learning for the Web. - Chuxu Zhang; Kaize Ding; Jundong Li; Dongkuan Xu; Haoyu Wang 004; Derek Zhiyuan Cheng; Huan Liu 001 (WWW (Companion Volume), 2025)

RelWeb 2025: The International Workshop on Resource-Efficient Learning for the Web. - Chuxu Zhang; Kaize Ding; Jundong Li; Dongkuan Xu; Haoyu Wang 004; Derek Zhiyuan Cheng; Huan Liu 001 (WWW (Companion Volume), 2025)

Leveraging Implicit Sentiments: Enhancing Reliability and Validity in Psychological Trait Evaluation of LLMs. - Huanhuan Ma; Haisong Gong; Xiaoyuan Yi; Xing Xie 001; Dongkuan Xu (CoRR, 2025)

AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference. - Shitong Duan; Xiaoyuan Yi; Peng Zhang 060; Dongkuan Xu; Jing Yao; Tun Lu; Ning Gu; Xing Xie 001 (CoRR, 2025)

Non-Overlap-Aware Egocentric Pose Estimation for Collaborative Perception in Connected Autonomy. - Hong Huang; Dongkuan Xu; Hao Zhang; Peng Gao (CoRR, 2025)

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs. - Travis Thompson; Seung-Hwan Lim; Paul Liu; Ruoying He; Dongkuan Xu (CoRR, 2025)