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ORCIDMing Liu 0028
Person information
- affiliation: Monash University, NCHA, Melbourne, Australia
- affiliation: Deakin University, School of Information Technology, Melbourne, Australia
- affiliation (PhD 2019): Monash University, Faculty of Information Technology, Melbourne, Australia
Other persons with the same name
- Ming Liu — disambiguation page
- Ming Liu 0001
![[0000-0002-4500-238X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-4500-238X")
— Hong Kong University of Science and Technology Guangzhou (HKUST-GZ), Guangzhou, China (and 4 more) - Ming Liu 0002 — University of Electronic Science and Technology of China, School of Computer Science and Engineering, Chengdu, China (and 1 more)
- Ming Liu 0003 — University of Electronic Science and Technology of China, School of Computer Science and Engineering, Chengdu, China
- Ming Liu 0004 — Harbin Institute of Technology, School of Computer Science and Technology, China
- Ming Liu 0005 — North Carolina State University, Neuromuscular Rehabilitation Engineering Laboratory, Raleigh, NC, USA (and 2 more)
- Ming Liu 0006 — University of Florida, Gainesville, FL, USA
- Ming Liu 0007 — University of Technology, Connected Intelligence Centre, Sydney, Australia (and 2 more)
- Ming Liu 0008 — Tongji University, School of Economics and Management, Shanghai, China
- Ming Liu 0009 — University of Illinois at Urbana-Champaign, Beckman Institute for Advanced Science and Technology, IL, USA (and 2 more)
- Ming Liu 0010 — Beijing Jiaotong University, Beijing Key Lab of Transportation Data Analysis and Mining, China (and 1 more)
- Ming Liu 0011 — Royal Institute of Technology, Stockholm, Sweden (and 1 more)
- Ming Liu 0012 — Shaanxi Normal University, School of Computer Science, Xi'an, China (and 2 more)
- Ming Liu 0013 — Princeton University, Department of Electrical Engineering, NJ, USA (and 1 more)
- Ming Liu 0014 — Harbin Institute of Technology, School of Astronautics, China (and 1 more)
- Ming Liu 0015 — Chinese Academy of Sciences, Institute of Semiconductors, State Key Laboratory on Integrated Optoelectronics, Beijing, China (and 2 more)
- Ming Liu 0017 — University of Electronic Science and Technology of China, School of Information and Communication Engineering, Chengdu, China (and 1 more)
- Ming Liu 0018 — Harbin Institute of Technolog, School of Computer Science and Technology, China
- Ming Liu 0019 — Hohai University, College of Computer and Information, Laboratory of Array and Information Processing, Nanjing, China
- Ming Liu 0020 — Beihang University, School of Biological Science and Medical Engineering, MOE Key Laboratory for Biomechanics and Mechanobiology, Beijing, China
- Ming Liu 0021 — Shanghai Jiao Tong University, Department of Electronic Engineering, Shanghai, China (and 1 more)
- Ming Liu 0022 — Chinese Academy Sciences, Institute of Microelectronics, Beijing, China
- Ming Liu 0023 — Hong Kong Polytechnic University, Department of Electrical Engineering, Hong Kong
- Ming Liu 0024 — Changchun University of Technology, Department of Applied Mathematics, Changchun, China
- Ming Liu 0025 — Shandong University of Science and Technology, Department of Electrical Engineering and Information Technology, Jinan, China
- Ming Liu 0026 — Xi'an Jiaotong University, State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China
- Ming Liu 0027 — University of Wisconsin at Madison, WI, USA (and 1 more)
- Ming Liu 0029 — Beijing Institute of Technology, Yangtze Delta Region Academy, School of Opto-Electronics, School of Optics and Photonics, China
- Ming Liu 0030 — Soochow University, Suzhou, China
- Ming Liu 0031 — Xidian University, Joint International Research Laboratory of Intelligent Perception and Computation, Xi'an, China
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2020 – today
- 2024
[j6]Stella Ho, Ming Liu, Shang Gao, Longxiang Gao:
Learning to learn for few-shot continual active learning. Artif. Intell. Rev. 57(10): 280 (2024)- [j5]Xiang Chen, Bo Liu, Shaofeng Zhao, Ming Liu, Hui Xu, Zhanbo Li, Zhigao Zheng:
ICT: Invisible Computable Trigger Backdoor Attacks in Transfer Learning. IEEE Trans. Consumer Electron. 70(4): 6747-6758 (2024) - [j4]Stella Ho, Ming Liu, Lan Du, Longxiang Gao, Yong Xiang:
Prototype-Guided Memory Replay for Continual Learning. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10973-10983 (2024) - [c18]Yangjie Tian, Xungang Gu, Aijia Li, He Zhang, Ruohua Xu, Yunfeng Li, Ming Liu:
Overview of the NLPCC2024 Shared Task 6: Scientific Literature Survey Generation. NLPCC (5) 2024: 400-408 - [i15]Ming Liu, Ran Liu, Ye Zhu, Hua Wang, Youyang Qu, Rongsheng Li, Yongpan Sheng, Wray L. Buntine:
A Survey on the Real Power of ChatGPT. CoRR abs/2405.00704 (2024) - 2023
- [j3]Huan Yee Koh, Jiaxin Ju, Ming Liu, Shirui Pan:
An Empirical Survey on Long Document Summarization: Datasets, Models, and Metrics. ACM Comput. Surv. 55(8): 154:1-154:35 (2023) - [c17]Xinzhe Li, Ming Liu, Shang Gao, Wray L. Buntine:
A Survey on Out-of-Distribution Evaluation of Neural NLP Models. IJCAI 2023: 6683-6691 - [i14]Xinzhe Li, Ming Liu, Shang Gao, Wray L. Buntine:
A Survey on Out-of-Distribution Evaluation of Neural NLP Models. CoRR abs/2306.15261 (2023) - [i13]Rundong Liu, Wenhan Liang, Weijun Luo, Yuxiang Song, He Zhang, Ruohua Xu, Yunfeng Li, Ming Liu:
Recent Advances in Hierarchical Multi-label Text Classification: A Survey. CoRR abs/2307.16265 (2023) - [i12]Stella Ho, Ming Liu, Shang Gao, Longxiang Gao:
Learning to Learn for Few-shot Continual Active Learning. CoRR abs/2311.03732 (2023) - 2022
- [j2]Junyi Chen, Lan Du, Ming Liu, Xiabing Zhou:
Mulan: A Multiple Residual Article-Wise Attention Network for Legal Judgment Prediction. ACM Trans. Asian Low Resour. Lang. Inf. Process. 21(4): 81:1-81:15 (2022) - [c16]Stella Ho, Ming Liu, Lan Du, Yunfeng Li, Longxiang Gao, Shang Gao:
Semi-supervised Continual Learning with Meta Self-training. CIKM 2022: 4024-4028 - [c15]Huan Yee Koh, Jiaxin Ju, He Zhang, Ming Liu, Shirui Pan:
How Far are We from Robust Long Abstractive Summarization? EMNLP 2022: 2682-2698 - [c14]Ming Liu, He Zhang, Yangjie Tian, Tianrui Zong, Borui Cai, Ruohua Xu, Yunfeng Li:
Overview of NLPCC2022 Shared Task 5 Track 1: Multi-label Classification for Scientific Literature. NLPCC (2) 2022: 320-327 - [c13]Borui Cai, He Zhang, Fenghong Liu, Ming Liu, Tianrui Zong, Zhe Chen, Yunfeng Li:
Overview of NLPCC2022 Shared Task 5 Track 2: Named Entity Recognition. NLPCC (2) 2022: 336-341 - [c12]Wei Hong, Jiao Yin, Mingshan You, Hua Wang, Jinli Cao, Jianxin Li, Ming Liu:
Graph Intelligence Enhanced Bi-Channel Insider Threat Detection. NSS 2022: 86-102 - [i11]Huan Yee Koh, Jiaxin Ju, Ming Liu, Shirui Pan:
An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics. CoRR abs/2207.00939 (2022) - [i10]Huan Yee Koh, Jiaxin Ju, He Zhang, Ming Liu, Shirui Pan:
How Far are We from Robust Long Abstractive Summarization? CoRR abs/2210.16732 (2022) - 2021
- [j1]Yuan Jin, Ming Liu, Yunfeng Li, Ruohua Xu, Lan Du, Longxiang Gao, Yong Xiang:
Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data. Data Min. Knowl. Discov. 35(2): 505-532 (2021) - [c11]Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine:
Neural Attention-Aware Hierarchical Topic Model. EMNLP (1) 2021: 1042-1052 - [c10]Kelvin Lo, Yuan Jin, Weicong Tan, Ming Liu, Lan Du, Wray L. Buntine:
Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence. EMNLP (Findings) 2021: 3334-3340 - [c9]Jiaxin Ju, Ming Liu, Huan Yee Koh, Yuan Jin, Lan Du, Shirui Pan:
Leveraging Information Bottleneck for Scientific Document Summarization. EMNLP (Findings) 2021: 4091-4098 - [i9]Ming Liu, Stella Ho, Mengqi Wang, Longxiang Gao, Yuan Jin, He Zhang:
Federated Learning Meets Natural Language Processing: A Survey. CoRR abs/2107.12603 (2021) - [i8]Stella Ho, Ming Liu, Lan Du, Longxiang Gao, Yong Xiang:
Prototypes-Guided Memory Replay for Continual Learning. CoRR abs/2108.12641 (2021) - [i7]Jiaxin Ju, Ming Liu, Huan Yee Koh, Yuan Jin, Lan Du, Shirui Pan:
Leveraging Information Bottleneck for Scientific Document Summarization. CoRR abs/2110.01280 (2021) - [i6]Kelvin Lo, Yuan Jin, Weicong Tan, Ming Liu, Lan Du, Wray L. Buntine:
Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence. CoRR abs/2110.07160 (2021) - [i5]Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine:
Neural Attention-Aware Hierarchical Topic Model. CoRR abs/2110.07161 (2021) - 2020
- [c8]Jiaxin Ju, Ming Liu, Longxiang Gao, Shirui Pan:
Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline. SDP@EMNLP 2020: 318-327 - [c7]Jueqing Lu, Lan Du, Ming Liu, Joanna Dipnall:
Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs. EMNLP (1) 2020: 2935-2943 - [c6]Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari:
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. SIGIR 2020: 1949-1952 - [i4]Yuan Jin, He Zhao, Ming Liu, Lan Du, Yunfeng Li, Ruohua Xu, Longxiang Gao:
Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering. CoRR abs/2002.09145 (2020) - [i3]Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari:
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. CoRR abs/2007.08954 (2020) - [i2]Jueqing Lu, Lan Du, Ming Liu, Joanna Dipnall:
Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs. CoRR abs/2010.07459 (2020) - [i1]Jiaxin Ju, Ming Liu, Longxiang Gao, Shirui Pan:
SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline. CoRR abs/2010.09190 (2020)
2010 – 2019
- 2019
- [b1]Ming Liu:
Weak Supervision and Active Learning for Natural Language Processing. Monash University, Australia, 2019 - [c5]Thuy-Trang Vu, Ming Liu, Dinh Phung, Gholamreza Haffari:
Learning How to Active Learn by Dreaming. ACL (1) 2019: 4091-4101 - 2018
- [c4]Ming Liu, Wray L. Buntine, Gholamreza Haffari:
Learning How to Actively Learn: A Deep Imitation Learning Approach. ACL (1) 2018: 1874-1883 - [c3]Ming Liu, Wray L. Buntine, Gholamreza Haffari:
Learning to Actively Learn Neural Machine Translation. CoNLL 2018: 334-344 - 2017
- [c2]Ming Liu, Gholamreza Haffari, Wray L. Buntine, Michelle Ananda-Rajah:
Leveraging Linguistic Resources for Improving Neural Text Classification. ALTA 2017: 34-42 - 2016
- [c1]Ming Liu, Gholamreza Haffari, Wray L. Buntine:
Learning cascaded latent variable models for biomedical text classification. ALTA 2016: 128-132
Coauthor Index
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