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Ming Gao 0001

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affiliation: East China Normal University, School of Data Science and Engineering, Shanghai, China
affiliation (former): Singapore Management University, Singapore

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Books and Theses

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2018
[b2]
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Ming Gao, Ee-Peng Lim, David Lo:
Network Data Mining and Analysis. East China Normal University Scientific Reports 8, WorldScientific 2018, ISBN 9789813274952, pp. 1-204
2017
[b1]
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Kun Yue, Weiyi Liu, Hao Wu, Dapeng Tao, Ming Gao:
Discovery and Fusion of Uncertain Knowledge in Data. East China Normal University Scientific Reports 6, WorldScientific 2017, ISBN 9789813227125, pp. 1-224

Journal Articles

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2024
[j16]
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Lei Li, Chengyu Wang, Minghui Qiu, Cen Chen, Ming Gao, Aoying Zhou:
Accelerating BERT inference with GPU-efficient exit prediction. Frontiers Comput. Sci. 18(3): 183308 (2024)
[j15]
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Jiacheng Liu, Feilong Tang, Zhijian Zheng, Hao Liu, Xiaofeng Hou, Long Chen, Ming Gao, Jiadi Yu, Yanmin Zhu:
Practical Network Modeling Using Weak Supervision Signals for Human-Centric Networking in Metaverse. IEEE J. Sel. Areas Commun. 42(3): 680-693 (2024)
[j14]
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Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao:
BapFL: You can Backdoor Personalized Federated Learning. ACM Trans. Knowl. Discov. Data 18(7): 166 (2024)
2023
[j13]
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Jiacheng Liu, Feilong Tang, Yanmin Zhu, Jiadi Yu, Long Chen, Ming Gao:
INFER: Distilling knowledge from human-generated rules with uncertainty for STINs. Inf. Sci. 645: 119219 (2023)
[j12]
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Lei Li, Tingting Liu, Chengyu Wang, Minghui Qiu, Cen Chen, Ming Gao, Aoying Zhou:
Resizing codebook of vector quantization without retraining. Multim. Syst. 29(3): 1499-1512 (2023)
[j11]
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Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua:
Learning Relation Prototype From Unlabeled Texts for Long-Tail Relation Extraction. IEEE Trans. Knowl. Data Eng. 35(2): 1761-1774 (2023)
2022
[j10]
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Jianbing Zheng, Ming Gao, Ee-Peng Lim, David Lo, Cheqing Jin, Aoying Zhou:
On measuring network robustness for weighted networks. Knowl. Inf. Syst. 64(7): 1967-1996 (2022)
[j9]
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Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou:
Learning Vertex Representations for Bipartite Networks. IEEE Trans. Knowl. Data Eng. 34(1): 379-393 (2022)
2019
[j8]
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Chao Kong, Ming Gao, Chen Xu, Yunbin Fu, Weining Qian, Aoying Zhou:
EnAli: entity alignment across multiple heterogeneous data sources. Frontiers Comput. Sci. 13(1): 157-169 (2019)
[j7]
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Jihong Yan, Chen Xu, Na Li, Ming Gao, Aoying Zhou:
Optimizing model parameter for entity summarization across knowledge graphs. J. Comb. Optim. 37(1): 293-318 (2019)
2018
[j6]
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Jihong Yan, Chengyu Wang, Wenliang Cheng, Ming Gao, Aoying Zhou:
A retrospective of knowledge graphs. Frontiers Comput. Sci. 12(1): 55-74 (2018)
2017
[j5]
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Xiangnan He, Ming Gao, Min-Yen Kan, Dingxian Wang:
BiRank: Towards Ranking on Bipartite Graphs. IEEE Trans. Knowl. Data Eng. 29(1): 57-71 (2017)
2016
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Ming Gao, Ee-Peng Lim, David Lo, Philips Kokoh Prasetyo:
On detecting maximal quasi antagonistic communities in signed graphs. Data Min. Knowl. Discov. 30(1): 99-146 (2016)
[j3]
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Rong Zhang, Ming Gao, Xiaofeng He, Aoying Zhou:
Learning user credibility for product ranking. Knowl. Inf. Syst. 46(3): 679-705 (2016)
2015
[j2]
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Jihong Yan, Wenliang Cheng, Chengyu Wang, Jun Liu, Ming Gao, Aoying Zhou:
Optimizing word set coverage for multi-event summarization. J. Comb. Optim. 30(4): 996-1015 (2015)
2014
[j1]
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Ming Gao, Cheqing Jin, Weining Qian, Xueqing Gong:
Real-time and Personalized Search over a Microblogging System. Comput. J. 57(9): 1281-1295 (2014)

Conference and Workshop Papers

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2025
[c76]
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Jiayi Wu, Hengyi Cai, Lingyong Yan, Hao Sun, Xiang Li, Shuaiqiang Wang, Dawei Yin, Ming Gao:
PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization. NAACL (Long Papers) 2025: 9091-9112
2024
[c75]
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Jianing Wang, Qiushi Sun, Xiang Li, Ming Gao:
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting. ACL (1) 2024: 4958-4981
[c74]
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Jianing Wang, Junda Wu, Yupeng Hou, Yao Liu, Ming Gao, Julian J. McAuley:
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment. ACL (Findings) 2024: 13492-13510
[c73]
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Chengcheng Han, Renyu Zhu, Jun Kuang, Fengjiao Chen, Xiang Li, Ming Gao, Xuezhi Cao, Yunsen Xian:
Conjoin after Decompose: Improving Few-Shot Performance of Named Entity Recognition. LREC/COLING 2024: 3707-3717
[c72]
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Qiushi Sun, Chengcheng Han, Nuo Chen, Renyu Zhu, Jingyang Gong, Xiang Li, Ming Gao:
Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives. LREC/COLING 2024: 10958-10969
[c71]
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Jiayi Wu, Renyu Zhu, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao:
Structure-aware Fine-tuning for Code Pre-trained Models. LREC/COLING 2024: 15362-15372
[c70]
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Qiushi Sun, Nuo Chen, Jianing Wang, Ming Gao, Xiang Li:
TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills. LREC/COLING 2024: 16713-16726
[c69]
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Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao:
Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence. ICASSP 2024: 7595-7599
[c68]
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Kangyang Luo, Shuai Wang, Yexuan Fu, Renrong Shao, Xiang Li, Yunshi Lan, Ming Gao, Jinlong Shu:
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning. ICDM 2024: 281-290
[c67]
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Jianing Wang, Chengyu Wang, Chuanqi Tan, Jun Huang, Ming Gao:
Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning. NAACL-HLT (Findings) 2024: 3261-3280
[c66]
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Jiayi Wu, Hao Sun, Hengyi Cai, Lixin Su, Shuaiqiang Wang, Dawei Yin, Xiang Li, Ming Gao:
Cross-model Control: Improving Multiple Large Language Models in One-time Training. NeurIPS 2024
[c65]
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Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao:
UPFL: Unsupervised Personalized Federated Learning towards New Clients. SDM 2024: 851-859
2023
[c64]
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Jianing Wang, Chengyu Wang, Jun Huang, Ming Gao, Aoying Zhou:
Uncertainty-Aware Self-Training for Low-Resource Neural Sequence Labeling. AAAI 2023: 13682-13690
[c63]
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Xiaodan Wang, Chengyu Wang, Lei Li, Zhixu Li, Ben Chen, Linbo Jin, Jun Huang, Yanghua Xiao, Ming Gao:
FashionKLIP: Enhancing E-Commerce Image-Text Retrieval with Fashion Multi-Modal Conceptual Knowledge Graph. ACL (industry) 2023: 149-158
[c62]
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Chengcheng Han, Liqing Cui, Renyu Zhu, Jianing Wang, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao:
When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario. ACL (Findings) 2023: 868-880
[c61]
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Jianing Wang, Nuo Chen, Qiushi Sun, Wenkang Huang, Chengyu Wang, Ming Gao:
HugNLP: A Unified and Comprehensive Library for Natural Language Processing. CIKM 2023: 5111-5116
[c60]
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Kangyang Luo, Xiang Li, Yunshi Lan, Ming Gao:
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting. CVPR 2023: 3708-3717
[c59]
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Tiandi Ye, Senhui Wei, Jamie Cui, Cen Chen, Yingnan Fu, Ming Gao:
Robust Clustered Federated Learning. DASFAA (1) 2023: 677-692
[c58]
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Chengcheng Han, Yuhe Wang, Yingnan Fu, Xiang Li, Minghui Qiu, Ming Gao, Aoying Zhou:
Meta-learning Siamese Network for Few-Shot Text Classification. DASFAA (3) 2023: 737-752
[c57]
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Kangyang Luo, Kunkun Zhang, Shengbo Zhang, Xiang Li, Ming Gao:
Decentralized Local Updates with Dual-Slow Estimation and Momentum-Based Variance-Reduction for Non-Convex Optimization. ECAI 2023: 1625-1632
[c56]
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Nuo Chen, Qiushi Sun, Jianing Wang, Xiang Li, Ming Gao:
Pass-Tuning: Towards Structure-Aware Parameter-Efficient Tuning for Code Representation Learning. EMNLP (Findings) 2023: 577-591
[c55]
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Jianing Wang, Qiushi Sun, Nuo Chen, Chengyu Wang, Jun Huang, Ming Gao, Xiang Li:
Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding. EMNLP (Findings) 2023: 7873-7884
[c54]
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Chengcheng Han, Xiaowei Du, Che Zhang, Yixin Lian, Xiang Li, Ming Gao, Baoyuan Wang:
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models. EMNLP 2023: 8055-8068
[c53]
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Nuo Chen, Qiushi Sun, Jianing Wang, Ming Gao, Xiaoli Li, Xiang Li:
Evaluating and Enhancing the Robustness of Code Pre-trained Models through Structure-Aware Adversarial Samples Generation. EMNLP (Findings) 2023: 14857-14873
[c52]
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Feilong Tang, Xue Li, Long Chen, Jiacheng Liu, Ming Gao, Yanqin Yang, Wenchao Xu, Heteng Zhang:
Reinforcement Learning Based Control Domain Division in LEO Satellite Networks. HPCC/DSS/SmartCity/DependSys 2023: 303-310
[c51]
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Yingfan Liu, Renyu Zhu, Ming Gao:
Personalized Programming Guidance Based on Deep Programming Learning Style Capturing. ICCSE (1) 2023: 214-231
[c50]
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Yao Liu, Tianran Liu, Chaopeng Yi, Yuepeng Xu, Ming Gao, Wei Wang, Aoying Zhou:
An Education-Oriented Collaborative Code Hosting Platform for Programming Courses. ICCSE (2) 2023: 304-315
[c49]
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Yingnan Fu, Tingting Liu, Ming Gao, Aoying Zhou:
EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition. ICDAR (1) 2023: 134-151
[c48]
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Minjie Chen, Yao Cheng, Ye Wang, Xiang Li, Ming Gao:
Graph Self-Contrast Representation Learning. ICDM 2023: 31-40
[c47]
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Moming Tang, Chengyu Wang, Jianing Wang, Cen Chen, Ming Gao, Weining Qian:
ParaSum: Contrastive Paraphrasing for Low-Resource Extractive Text Summarization. KSEM (3) 2023: 106-119
[c46]
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Yingnan Fu, Wenyuan Cai, Ming Gao, Aoying Zhou:
Symbol Location-Aware Network for Improving Handwritten Mathematical Expression Recognition. ICMR 2023: 516-524
[c45]
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Yingnan Fu, Shu Zheng, Wenyuan Cai, Ming Gao, Cheqing Jin, Aoying Zhou:
Dynamic Feature Selection for Structural Image Content Recognition. MMM (2) 2023: 337-349
[c44]
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Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao:
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning. NeurIPS 2023
[c43]
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Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao:
SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. WWW 2023: 143-153
2022
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Renyu Zhu, Lei Yuan, Xiang Li, Ming Gao, Wenyuan Cai:
A Neural Network Architecture for Program Understanding Inspired by Human Behaviors. ACL (1) 2022: 5142-5153
[c41]
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Cen Chen, Tiandi Ye, Li Wang, Ming Gao:
Learning to Generalize in Heterogeneous Federated Networks. CIKM 2022: 159-168
[c40]
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Jianing Wang, Chengyu Wang, Fuli Luo, Chuanqi Tan, Minghui Qiu, Fei Yang, Qiuhui Shi, Songfang Huang, Ming Gao:
Towards Unified Prompt Tuning for Few-shot Text Classification. EMNLP (Findings) 2022: 524-536
[c39]
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Tingting Liu, Chengyu Wang, Xiangru Zhu, Lei Li, Minghui Qiu, Jun Huang, Ming Gao, Yanghua Xiao:
ARTIST: A Transformer-based Chinese Text-to-Image Synthesizer Digesting Linguistic and World Knowledge. EMNLP (Findings) 2022: 881-888
[c38]
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Jianing Wang, Chengyu Wang, Minghui Qiu, Qiuhui Shi, Hongbin Wang, Jun Huang, Ming Gao:
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering. EMNLP 2022: 3152-3163
[c37]
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Jianing Wang, Wenkang Huang, Minghui Qiu, Qiuhui Shi, Hongbin Wang, Xiang Li, Ming Gao:
Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding. EMNLP 2022: 3164-3177
[c36]
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Jianing Wang, Chengyu Wang, Chuanqi Tan, Minghui Qiu, Songfang Huang, Jun Huang, Ming Gao:
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition. EMNLP 2022: 3466-3476
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Nuo Chen, Qiushi Sun, Renyu Zhu, Xiang Li, Xuesong Lu, Ming Gao:
CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure. EMNLP (Findings) 2022: 4000-4008
[c34]
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Renyu Zhu, Dongxiang Zhang, Chengcheng Han, Ming Gao, Xuesong Lu, Weining Qian, Aoying Zhou:
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model. ICDM (Workshops) 2022: 298-307
[c33]
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Tingting Liu, Chengyu Wang, Cen Chen, Ming Gao, Aoying Zhou:
Understanding Long Programming Languages with Structure-Aware Sparse Attention. SIGIR 2022: 2093-2098
[c32]
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Lei Li, Dongxiang Zhang, Chengyu Wang, Cheqing Jin, Ming Gao, Aoying Zhou:
Enhancing Seq2seq Math Word Problem Solver with Entity Information and Math Knowledge. WISE 2022: 370-385
2021
[c31]
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Chengcheng Han, Zeqiu Fan, Dongxiang Zhang, Minghui Qiu, Ming Gao, Aoying Zhou:
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification. ACL/IJCNLP (Findings) 2021: 1664-1673
[c30]
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Chengyu Wang, Jianing Wang, Minghui Qiu, Jun Huang, Ming Gao:
TransPrompt: Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification. EMNLP (1) 2021: 2792-2802
[c29]
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Jianbing Zheng, Shuai Wang, Cheqing Jin, Ming Gao, Aoying Zhou, Liang Ni:
Trajectory Similarity Search with Multi-level Semantics. ICA3PP (3) 2021: 602-619
[c28]
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Na Li, Renyu Zhu, Xiaoxu Zhou, Xiangnan He, Wenyuan Cai, Ming Gao, Aoying Zhou:
On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner. ICDE 2021: 888-899
2020
[c27]
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Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou:
Improving Neural Relation Extraction with Implicit Mutual Relations. ICDE 2020: 1021-1032
2019
[c26]
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  - conf/ccis/AiGZ019
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Lisi Ai, Baoli Gao, Jianbing Zheng, Ming Gao:
On Improving Text Generation Via Integrating Text Coherence. CCIS 2019: 6-10
[c25]
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Yuanzhe Chen, Jun Kuang, Dawei Cheng, Jianbin Zheng, Ming Gao, Aoying Zhou:
AgriKG: An Agricultural Knowledge Graph and Its Applications. DASFAA (3) 2019: 533-537
2018
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Ming Gao, Leihui Chen, Xiangnan He, Aoying Zhou:
BiNE: Bipartite Network Embedding. SIGIR 2018: 715-724
2017
[c23]
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Lisi Ai, Na Li, Jianbing Zheng, Ming Gao:
Automatic Text Generation via Text Extraction Based on Submodular. APWeb/WAIM Workshops 2017: 237-246
[c22]
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Leihui Chen, Jianbing Zheng, Ming Gao, Aoying Zhou, Wei Zeng, Hui Chen:
TLRec: Transfer Learning for Cross-Domain Recommendation. ICBK 2017: 167-172
[c21]
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Jianbing Zheng, Yanbin Li, Yanji Hou, Ming Gao, Aoying Zhou:
BMNR: Design and Implementation a Benchmark for Metrics of Network Robustness. ICBK 2017: 320-325
2016
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Liang Zhang, Ming Gao, Weining Qian, Aoying Zhou:
Compressing Streaming Graph Data Based on Triangulation. APWeb Workshops 2016: 164-175
[c19]
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Chao Kong, Ming Gao, Chen Xu, Weining Qian, Aoying Zhou:
Entity Matching Across Multiple Heterogeneous Data Sources. DASFAA (1) 2016: 133-146
[c18]
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Jihong Yan, Yanhua Wang, Ming Gao, Aoying Zhou:
Context-Aware Entity Summarization. WAIM (1) 2016: 517-529
2015
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Chao Kong, Ming Gao, Weining Qian, Minqi Zhou, Xueqing Gong, Rong Zhang, Aoying Zhou:
ACID Encountering the CAP Theorem: Two Bank Case Studies. IEEE WISA 2015: 235-240
[c16]
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Jinyang Li, Chengyu Wang, Xiaofeng He, Rong Zhang, Ming Gao:
User Generated Content Oriented Chinese Taxonomy Construction. APWeb 2015: 623-634
[c15]
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Chengyu Wang, Ming Gao, Xiaofeng He, Rong Zhang:
Challenges in Chinese knowledge graph construction. ICDE Workshops 2015: 59-61
[c14]
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Qiuge Song, Cheqing Jin, Xiaoling Wang, Ming Gao, Aoying Zhou:
Discovering underpasses from walking trajectories. ICDE Workshops 2015: 129-133
[c13]
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Ming Gao, Ee-Peng Lim, David Lo, Feida Zhu, Philips Kokoh Prasetyo, Aoying Zhou:
CNL: Collective Network Linkage Across Heterogeneous Social Platforms. ICDM 2015: 757-762
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Rong Zhang, Yifan Gao, Wenzhe Yu, Pingfu Chao, Xiaoyan Yang, Ming Gao, Aoying Zhou:
Review Comment Analysis for Predicting Ratings. WAIM 2015: 247-259
[c11]
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Lei Wang, Ming Gao, Rong Zhang, Cheqing Jin, Aoying Zhou:
Computing Probability Threshold Set Similarity on Probabilistic Sets. WAIM 2015: 374-386
2014
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Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama:
Predicting the popularity of web 2.0 items based on user comments. SIGIR 2014: 233-242
2013
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Ming Gao, Cheqing Jin, Wei Wang, Xuemin Lin, Aoying Zhou:
Similarity query processing for probabilistic sets. ICDE 2013: 913-924
[c8]
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Philips Kokoh Prasetyo, Ming Gao, Ee-Peng Lim, Christie Napa Scollon:
Social Sensing for Urban Crisis Management: The Case of Singapore Haze. SocInfo 2013: 478-491
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Ming Gao, Ee-Peng Lim, David Lo:
R-energy for evaluating robustness of dynamic networks. WebSci 2013: 89-98
2012
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Ming Gao, Cheqing Jin, Weining Qian, Xueqing Gong:
Real-Time Search over a Microblogging System. CGC 2012: 352-359
2011
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Cheqing Jin, Ming Gao, Aoying Zhou:
Handling ER-topk Query on Uncertain Streams. DASFAA (1) 2011: 326-340
2010
[c4]
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Ming Gao, Xiangnan He, Cheqing Jin, Xiaoling Wang, Aoying Zhou:
Recording How-Provenance on Probabilistic Databases. APWeb 2010: 205-211
[c3]
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Peisen Yuan, Xiaoling Wang, Chaofeng Sha, Ming Gao, Aoying Zhou:
GRAMS³: An Efficient Framework for XML Structural Similarity Search. DASFAA Workshops 2010: 422-433
2009
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Chen Zhang, Ming Gao, Aoying Zhou:
Tracking High Quality Clusters over Uncertain Data Streams. ICDE 2009: 1641-1648
2004
[c1]
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Jiadi Yu, Minglu Li, Ying Li, Feng Hong, Ming Gao:
A Framework for Price-Based Resource Allocation on the Grid. PDCAT 2004: 341-344

Informal and Other Publications

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2024
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Yunshi Lan, Xinyuan Li, Hanyue Du, Xuesong Lu, Ming Gao, Weining Qian, Aoying Zhou:
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends. CoRR abs/2401.07518 (2024)
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  - journals/corr/abs-2402-08785
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Jianing Wang, Junda Wu, Yupeng Hou, Yao Liu, Ming Gao, Julian J. McAuley:
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment. CoRR abs/2402.08785 (2024)
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  - journals/corr/abs-2403-14638
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Yingfan Liu, Renyu Zhu, Ming Gao:
Personalized Programming Guidance based on Deep Programming Learning Style Capturing. CoRR abs/2403.14638 (2024)
[i42]
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Jiayi Wu, Renyu Zhu, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao:
Structure-aware Fine-tuning for Code Pre-trained Models. CoRR abs/2404.07471 (2024)
[i41]
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  - journals/corr/abs-2409-06955
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Kangyang Luo, Shuai Wang, Xiang Li, Yunshi Lan, Ming Gao, Jinlong Shu:
Privacy-Preserving Federated Learning with Consistency via Knowledge Distillation Using Conditional Generator. CoRR abs/2409.06955 (2024)
[i40]
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  - journals/corr/abs-2409-07734
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Kangyang Luo, Shuai Wang, Yexuan Fu, Renrong Shao, Xiang Li, Yunshi Lan, Ming Gao, Jinlong Shu:
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning. CoRR abs/2409.07734 (2024)
[i39]
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  - journals/corr/abs-2410-17599
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Jiayi Wu, Hao Sun, Hengyi Cai, Lixin Su, Shuaiqiang Wang, Dawei Yin, Xiang Li, Ming Gao:
Cross-model Control: Improving Multiple Large Language Models in One-time Training. CoRR abs/2410.17599 (2024)
[i38]
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  - journals/corr/abs-2412-14510
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Jiayi Wu, Hengyi Cai, Lingyong Yan, Hao Sun, Xiang Li, Shuaiqiang Wang, Dawei Yin, Ming Gao:
PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization. CoRR abs/2412.14510 (2024)
2023
[i37]
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  - journals/corr/abs-2301-12458
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Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao:
Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking. CoRR abs/2301.12458 (2023)
[i36]
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  - journals/corr/abs-2302-03507
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Chengcheng Han, Yuhe Wang, Yingnan Fu, Xiang Li, Minghui Qiu, Ming Gao, Aoying Zhou:
Meta-Learning Siamese Network for Few-Shot Text Classification. CoRR abs/2302.03507 (2023)
[i35]
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  - journals/corr/abs-2302-07739
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Chengcheng Han, Renyu Zhu, Jun Kuang, Fengjiao Chen, Xiang Li, Ming Gao, Xuezhi Cao, Wei Wu:
Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity Recognition. CoRR abs/2302.07739 (2023)
[i34]
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  - journals/corr/abs-2302-08659
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Jianing Wang, Chengyu Wang, Jun Huang, Ming Gao, Aoying Zhou:
Uncertainty-aware Self-training for Low-resource Neural Sequence Labeling. CoRR abs/2302.08659 (2023)
[i33]
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  - journals/corr/abs-2302-14286
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Jianing Wang, Nuo Chen, Qiushi Sun, Wenkang Huang, Chengyu Wang, Ming Gao:
HugNLP: A Unified and Comprehensive Library for Natural Language Processing. CoRR abs/2302.14286 (2023)
[i32]
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Kangyang Luo, Xiang Li, Yunshi Lan, Ming Gao:
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting. CoRR abs/2302.14307 (2023)
[i31]
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  - journals/corr/abs-2305-08088
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Qiushi Sun, Chengcheng Han, Nuo Chen, Renyu Zhu, Jingyang Gong, Xiang Li, Ming Gao:
Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives. CoRR abs/2305.08088 (2023)
[i30]
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  - journals/corr/abs-2305-10013
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Chengcheng Han, Liqing Cui, Renyu Zhu, Jianing Wang, Nuo Chen, Qiushi Sun, Xiang Li, Ming Gao:
When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario. CoRR abs/2305.10013 (2023)
[i29]
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  - journals/corr/abs-2306-06427
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Jianing Wang, Qiushi Sun, Nuo Chen, Xiang Li, Ming Gao:
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting. CoRR abs/2306.06427 (2023)
[i28]
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  - journals/corr/abs-2306-07285
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Qiushi Sun, Nuo Chen, Jianing Wang, Xiang Li, Ming Gao:
TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills. CoRR abs/2306.07285 (2023)
[i27]
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Kangyang Luo, Kunkun Zhang, Shengbo Zhang, Xiang Li, Ming Gao:
Decentralized Local Updates with Dual-Slow Estimation and Momentum-based Variance-Reduction for Non-Convex Optimization. CoRR abs/2307.08299 (2023)
[i26]
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  - journals/corr/abs-2307-15971
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Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao:
You Can Backdoor Personalized Federated Learning. CoRR abs/2307.15971 (2023)
[i25]
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  - journals/corr/abs-2307-15994
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Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao:
UPFL: Unsupervised Personalized Federated Learning towards New Clients. CoRR abs/2307.15994 (2023)
[i24]
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Jianing Wang, Chengyu Wang, Cen Chen, Ming Gao, Jun Huang, Aoying Zhou:
TransPrompt v2: A Transferable Prompting Framework for Cross-task Text Classification. CoRR abs/2308.15010 (2023)
[i23]
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  - journals/corr/abs-2309-02190
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Renyu Zhu, Chengcheng Han, Yong Qian, Qiushi Sun, Xiang Li, Ming Gao, Xuezhi Cao, Yunsen Xian:
Exchanging-based Multimodal Fusion with Transformer. CoRR abs/2309.02190 (2023)
[i22]
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Minjie Chen, Yao Cheng, Ye Wang, Xiang Li, Ming Gao:
Graph Self-Contrast Representation Learning. CoRR abs/2309.02304 (2023)
[i21]
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  - journals/corr/abs-2309-13546
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Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao:
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning. CoRR abs/2309.13546 (2023)
[i20]
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  - journals/corr/abs-2309-14771
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Jianing Wang, Chengyu Wang, Chuanqi Tan, Jun Huang, Ming Gao:
Boosting In-Context Learning with Factual Knowledge. CoRR abs/2309.14771 (2023)
[i19]
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  - journals/corr/abs-2310-05074
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Chengcheng Han, Xiaowei Du, Che Zhang, Yixin Lian, Xiang Li, Ming Gao, Baoyuan Wang:
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models. CoRR abs/2310.05074 (2023)
[i18]
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  - journals/corr/abs-2310-13022
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Jianing Wang, Qiushi Sun, Nuo Chen, Chengyu Wang, Jun Huang, Ming Gao, Xiang Li:
Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding. CoRR abs/2310.13022 (2023)
[i17]
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  - journals/corr/abs-2311-02832
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Yao Cheng, Minjie Chen, Xiang Li, Caihua Shan, Ming Gao:
Prioritized Propagation in Graph Neural Networks. CoRR abs/2311.02832 (2023)
[i16]
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  - journals/corr/abs-2311-12358
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Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao:
Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence. CoRR abs/2311.12358 (2023)
2022
[i15]
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Jianing Wang, Chengyu Wang, Minghui Qiu, Qiuhui Shi, Hongbin Wang, Jun Huang, Ming Gao:
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering. CoRR abs/2205.03071 (2022)
[i14]
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  - journals/corr/abs-2205-05313
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Jianing Wang, Chengyu Wang, Fuli Luo, Chuanqi Tan, Minghui Qiu, Fei Yang, Qiuhui Shi, Songfang Huang, Ming Gao:
Towards Unified Prompt Tuning for Few-shot Text Classification. CoRR abs/2205.05313 (2022)
[i13]
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Tingting Liu, Chengyu Wang, Cen Chen, Ming Gao, Aoying Zhou:
Understanding Long Programming Languages with Structure-Aware Sparse Attention. CoRR abs/2205.13730 (2022)
[i12]
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Renyu Zhu, Lei Yuan, Xiang Li, Ming Gao, Wenyuan Cai:
A Neural Network Architecture for Program Understanding Inspired by Human Behaviors. CoRR abs/2206.04730 (2022)
[i11]
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  - journals/corr/abs-2210-04633
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Nuo Chen, Qiushi Sun, Renyu Zhu, Xiang Li, Xuesong Lu, Ming Gao:
CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure. CoRR abs/2210.04633 (2022)
[i10]
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  - journals/corr/abs-2210-08536
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Jianing Wang, Wenkang Huang, Qiuhui Shi, Hongbin Wang, Minghui Qiu, Xiang Li, Ming Gao:
Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding. CoRR abs/2210.08536 (2022)
[i9]
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  - journals/corr/abs-2210-09049
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Jianing Wang, Chengyu Wang, Chuanqi Tan, Minghui Qiu, Songfang Huang, Jun Huang, Ming Gao:
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition. CoRR abs/2210.09049 (2022)
2021
[i8]
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  - journals/corr/abs-2107-12262
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Chengcheng Han, Zeqiu Fan, Dongxiang Zhang, Minghui Qiu, Ming Gao, Aoying Zhou:
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification. CoRR abs/2107.12262 (2021)
[i7]
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  - journals/corr/abs-2112-08273
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Renyu Zhu, Dongxiang Zhang, Chengcheng Han, Ming Gao, Xuesong Lu, Weining Qian, Aoying Zhou:
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model. CoRR abs/2112.08273 (2021)
2020
[i6]
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  - journals/corr/abs-2007-02517
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Yingnan Fu, Tingting Liu, Ming Gao, Aoying Zhou:
EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition. CoRR abs/2007.02517 (2020)
[i5]
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  - journals/corr/abs-2011-13574
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Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua:
Learning Relation Prototype from Unlabeled Texts for Long-tail Relation Extraction. CoRR abs/2011.13574 (2020)
[i4]
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  - journals/corr/abs-2011-14333
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Na Li, Renyu Zhu, Xiaoxu Zhou, Xiangnan He, Wenyuan Cai, Ming Gao, Aoying Zhou:
On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner. CoRR abs/2011.14333 (2020)
2019
[i3]
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  - journals/corr/abs-1901-09676
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Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou:
Learning Vertex Representations for Bipartite Networks. CoRR abs/1901.09676 (2019)
[i2]
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  - journals/corr/abs-1907-05333
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Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou:
Improving Neural Relation Extraction with Implicit Mutual Relations. CoRR abs/1907.05333 (2019)
2017
[i1]
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  - journals/corr/abs-1708-04396
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Xiangnan He, Ming Gao, Min-Yen Kan, Dingxian Wang:
BiRank: Towards Ranking on Bipartite Graphs. CoRR abs/1708.04396 (2017)

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