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ORCIDLingfei Wu 0001
吴凌飞
Person information
- unicode name: 吴凌飞
- affiliation: Anytime.AI, USA
- affiliation (former): Pinterest Inc., Francisco, CA, USA
- affiliation (former): JD.COM, Silicon Valley Research Center, Mountain View, CA, USA
- affiliation (former): IBM Research, Thomas J. Watson Research Center, Yorktown Heights, NY, USA
- affiliation (PhD 2016): College of William and Mary, Department of Computer Science, Williamsburg, VA, USA
- affiliation (former): University of Science and Technology of China, Department of Automation, Hefei, China
Other persons with the same name
- Lingfei Wu 0002
![[0000-0002-0102-3613]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-0102-3613")
— University of Pittsburgh, School of Computing and Information, PA, USA (and 3 more) - Lingfei Wu 0003 — Hangzhou Dianzi University, College of Computer, China
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Journal Articles
- 2024
[j28]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks. ACM Comput. Surv. 56(5): 126:1-126:42 (2024)- [j27]Jing Hu, Lingfei Wu, Yu Chen, Po Hu, Mohammed J. Zaki:
GraphFlow+: Exploiting Conversation Flow in Conversational Machine Comprehension with Graph Neural Networks. Mach. Intell. Res. 21(2): 272-282 (2024) - [j26]Kai Shen, Lingfei Wu, Siliang Tang, Fangli Xu, Bo Long, Yueting Zhuang, Jian Pei:
Ask Questions With Double Hints: Visual Question Generation With Answer-Awareness and Region-Reference. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 9648-9660 (2024) - [j25]Pengwei Xing, Songtao Lu, Lingfei Wu, Han Yu:
BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning. IEEE Trans. Big Data 10(6): 903-914 (2024) - [j24]Zhuo Zhao, Guangyou Zhou, Zhiwen Xie, Lingfei Wu, Jimmy Xiangji Huang:
CGKPN: Cross-Graph Knowledge Propagation Network with Adaptive Connection for Reasoning-Based Machine Reading Comprehension. ACM Trans. Intell. Syst. Technol. 15(4): 70:1-70:24 (2024) - [j23]Jianhao Guo, Siliang Tang, Juncheng Li, Kaihang Pan, Lingfei Wu:
RustGraph: Robust Anomaly Detection in Dynamic Graphs by Jointly Learning Structural-Temporal Dependency. IEEE Trans. Knowl. Data Eng. 36(7): 3472-3485 (2024) - [j22]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12706-12717 (2024) - [j21]Cuiying Huo, Dongxiao He, Chundong Liang, Di Jin, Tie Qiu, Lingfei Wu:
TrustGNN: Graph Neural Network-Based Trust Evaluation via Learnable Propagative and Composable Nature. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14205-14217 (2024) - [j20]Zhizhi Yu, Di Jin, Jianguo Wei, Yawen Li, Ziyang Liu, Yue Shang, Jiawei Han, Lingfei Wu:
TeKo: Text-Rich Graph Neural Networks With External Knowledge. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14699-14711 (2024) - [j19]Qi Shen, Lingfei Wu, Yiming Zhang, Yitong Pang, Zhihua Wei, Fangli Xu, Bo Long, Jian Pei:
Multi-Interest Multi-Round Conversational Recommendation System with Fuzzy Feedback Based User Simulator. Trans. Recomm. Syst. 2(4): 27:1-27:29 (2024) - 2023
- [j18]Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Jianchao Lu, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent online selling point extraction and generation for e-commerce recommendation. AI Mag. 44(1): 16-29 (2023) - [j17]Yanyan Zou, Xueying Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Mian Ma, Sulong Xu, Han Yu, Lingfei Wu:
Automatic product copywriting for e-commerce. AI Mag. 44(1): 41-53 (2023) - [j16]Xiang Ling, Lingfei Wu, Jiangyu Zhang, Zhenqing Qu, Wei Deng, Xiang Chen, Yaguan Qian, Chunming Wu, Shouling Ji, Tianyue Luo, Jingzheng Wu, Yanjun Wu:
Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art. Comput. Secur. 128: 103134 (2023) - [j15]Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. Found. Trends Mach. Learn. 16(2): 119-328 (2023) - [j14]Yuyang Gao, Tanmoy Chowdhury, Lingfei Wu, Liang Zhao:
Modeling Health Stage Development of Patients With Dynamic Attributed Graphs in Online Health Communities. IEEE Trans. Knowl. Data Eng. 35(2): 1831-1843 (2023) - [j13]Xiang Ling, Lingfei Wu, Saizhuo Wang, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Multilevel Graph Matching Networks for Deep Graph Similarity Learning. IEEE Trans. Neural Networks Learn. Syst. 34(2): 799-813 (2023) - [j12]Xiaojie Guo, Lingfei Wu, Liang Zhao:
Deep Graph Translation. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8225-8234 (2023) - [j11]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long:
Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation. Trans. Recomm. Syst. 1(4): 1-22 (2023) - 2022
- [j10]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu:
Knowledge-aware document summarization: A survey of knowledge, embedding methods and architectures. Knowl. Based Syst. 257: 109882 (2022) - [j9]Hanlu Wu, Tengfei Ma, Lingfei Wu, Fangli Xu, Shouling Ji:
Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing. ACM Trans. Knowl. Discov. Data 16(2): 27:1-27:18 (2022) - [j8]April Yi Wang, Dakuo Wang, Jaimie Drozdal, Michael J. Muller, Soya Park, Justin D. Weisz, Xuye Liu, Lingfei Wu, Casey Dugan:
Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks. ACM Trans. Comput. Hum. Interact. 29(2): 17:1-17:33 (2022) - 2021
- [j7]Xiang Ling, Lingfei Wu, Saizhuo Wang, Gaoning Pan, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Deep Graph Matching and Searching for Semantic Code Retrieval. ACM Trans. Knowl. Discov. Data 15(5): 88:1-88:21 (2021) - [j6]Qingzhe Li, Amir Alipour-Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, Liang Zhao:
Large-scale Cost-Aware Classification Using Feature Computational Dependency Graph. IEEE Trans. Knowl. Data Eng. 33(5): 2029-2044 (2021) - 2019
- [j5]Lingfei Wu, Fei Xue, Andreas Stathopoulos:
TRPL+K: Thick-Restart Preconditioned Lanczos+K Method for Large Symmetric Eigenvalue Problems. SIAM J. Sci. Comput. 41(2): A1013-A1040 (2019) - 2017
- [j4]Lingfei Wu, Eloy Romero, Andreas Stathopoulos:
PRIMME_SVDS: A High-Performance Preconditioned SVD Solver for Accurate Large-Scale Computations. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j3]Lingfei Wu, Jesse Laeuchli, Vassilis Kalantzis, Andreas Stathopoulos, Efstratios Gallopoulos:
Estimating the trace of the matrix inverse by interpolating from the diagonal of an approximate inverse. J. Comput. Phys. 326: 828-844 (2016) - [j2]Lingfei Wu, K. John Wu, Alex Sim, Michael Churchill, Jong Youl Choi, Andreas Stathopoulos, Choong-Seock Chang, Scott Klasky:
Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma. IEEE Trans. Big Data 2(3): 262-275 (2016) - 2015
- [j1]Lingfei Wu, Andreas Stathopoulos:
A Preconditioned Hybrid SVD Method for Accurately Computing Singular Triplets of Large Matrices. SIAM J. Sci. Comput. 37(5) (2015)
Conference and Workshop Papers
- 2024
- [c98]Ruoqi Liu, Lingfei Wu, Ping Zhang:
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs. AAAI 2024: 8805-8814 - [c97]Yangkai Du, Tengfei Ma, Lingfei Wu, Xuhong Zhang, Shouling Ji:
AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection. AAAI 2024: 17942-17950 - [c96]Zefan Wang, Zichuan Liu, Yingying Zhang, Aoxiao Zhong, Jihong Wang, Fengbin Yin, Lunting Fan, Lingfei Wu, Qingsong Wen:
RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models. CIKM 2024: 4966-4974 - [c95]Xiaoqiang Wang, Lingfei Wu, Tengfei Ma, Bang Liu:
FAC²E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition. EMNLP 2024: 13228-13243 - [c94]Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Shouling Ji, Wenhai Wang:
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. NAACL-HLT (Findings) 2024: 2959-2971 - [c93]Vachik S. Dave, Linsey Pang, Xiquan Cui, Chen Luo, Hamed Zamani, Lingfei Wu, George Karypis:
The 3rd International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom 2024). WSDM 2024: 1208-1209 - 2023
- [c92]Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu:
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation. AAAI 2023: 4339-4346 - [c91]Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu:
Human-Instructed Deep Hierarchical Generative Learning for Automated Urban Planning. AAAI 2023: 4660-4667 - [c90]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
SkillQG: Learning to Generate Question for Reading Comprehension Assessment. ACL (Findings) 2023: 13833-13850 - [c89]Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Fei Qi, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li, Hongmin Cai:
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training. BIBM 2023: 1294-1299 - [c88]Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Shouling Ji, Wenhai Wang:
CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code. EMNLP 2023: 14740-14752 - [c87]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2023: 5831-5832 - [c86]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). KDD 2023: 5891-5892 - [c85]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 - [c84]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. WSDM 2023: 222-230 - [c83]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c82]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. WWW 2023: 727-736 - [c81]Vachik S. Dave, Linsey Pang, Xiquan Cui, Lingfei Wu, Hamed Zamani, George Karypis:
The 2nd Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom). WWW (Companion Volume) 2023: 850-853 - 2022
- [c80]Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Jianchao Lu, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent Online Selling Point Extraction for E-commerce Recommendation. AAAI 2022: 12360-12368 - [c79]Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Automatic Product Copywriting for E-commerce. AAAI 2022: 12423-12431 - [c78]Xiaoqiang Wang, Bang Liu, Fangli Xu, Bo Long, Siliang Tang, Lingfei Wu:
Feeding What You Need by Understanding What You Learned. ACL (1) 2022: 5858-5874 - [c77]Linsey Pang, Wei Liu, Lingfei Wu, Kexin Xie, Stephen D. Guo, Raghav Chalapathy, Musen Wen:
Applied Machine Learning Methods for Time Series Forecasting. CIKM 2022: 5175-5176 - [c76]Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang:
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search. EMNLP (Industry Track) 2022: 63-76 - [c75]Peng Lin, Yanyan Zou, Lingfei Wu, Mian Ma, Zhuoye Ding, Bo Long:
Automatic Scene-based Topic Channel Construction System for E-Commerce. EMNLP (Industry Track) 2022: 272-284 - [c74]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
QRelScore: Better Evaluating Generated Questions with Deeper Understanding of Context-aware Relevance. EMNLP 2022: 562-581 - [c73]Dong Chen, Lingfei Wu, Siliang Tang, Xiao Yun, Bo Long, Yueting Zhuang:
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile. ICML 2022: 3662-3678 - [c72]Jiayin Jin, Zeru Zhang, Yang Zhou, Lingfei Wu:
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing. ICML 2022: 10340-10361 - [c71]Hanning Gao, Lingfei Wu, Po Hu, Zhihua Wei, Fangli Xu, Bo Long:
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph. AACL/IJCNLP (1) 2022: 82-92 - [c70]Xiang Ling, Lingfei Wu, Wei Deng, Zhenqing Qu, Jiangyu Zhang, Sheng Zhang, Tengfei Ma, Bin Wang, Chunming Wu, Shouling Ji:
MalGraph: Hierarchical Graph Neural Networks for Robust Windows Malware Detection. INFOCOM 2022: 1998-2007 - [c69]Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Generation of Product-Image Sequence in E-commerce. KDD 2022: 2851-2859 - [c68]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. KDD 2022: 2946-2956 - [c67]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2022: 4840-4841 - [c66]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2022). KDD 2022: 4906-4907 - [c65]Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long, Jian Pei:
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation. WSDM 2022: 775-783 - [c64]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c63]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. WWW 2022: 1601-1610 - [c62]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Bo Long, Jian Pei:
Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation. WWW 2022: 2153-2162 - 2021
- [c61]Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu:
Relation-aware Graph Attention Model with Adaptive Self-adversarial Training. AAAI 2021: 9368-9376 - [c60]Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang:
Sequential Search with Off-Policy Reinforcement Learning. CIKM 2021: 4006-4015 - [c59]Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Bo Long, Shouling Ji:
Constructing contrastive samples via summarization for text classification with limited annotations. EMNLP (Findings) 2021: 1365-1376 - [c58]Xuye Liu, Dakuo Wang, April Yi Wang, Yufang Hou, Lingfei Wu:
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks. EMNLP (Findings) 2021: 4473-4485 - [c57]Zeru Zhang, Zijie Zhang, Yang Zhou, Lingfei Wu, Sixing Wu, Xiaoying Han, Dejing Dou, Tianshi Che, Da Yan:
Adversarial Attack against Cross-lingual Knowledge Graph Alignment. EMNLP (1) 2021: 5320-5337 - [c56]Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen R. McKeown:
Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport. EMNLP (1) 2021: 6443-6456 - [c55]Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan:
Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks. ICML 2021: 12719-12735 - [c54]April Yi Wang, Dakuo Wang, Xuye Liu, Lingfei Wu:
Graph-Augmented Code Summarization in Computational Notebooks. IJCAI 2021: 5020-5023 - [c53]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c52]Lingfei Wu, Yu Chen, Heng Ji, Bang Liu:
Deep Learning on Graphs for Natural Language Processing. KDD 2021: 4084-4085 - [c51]Lingfei Wu, Jiliang Tang, Yinglong Xia, Jian Pei, Xiaojie Guo:
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). KDD 2021: 4167-4168 - [c50]Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu:
2nd International Workshop on Industrial Recommendation Systems (IRS). KDD 2021: 4173-4174 - [c49]Shiwei Wu, Joya Chen, Tong Xu, Liyi Chen, Lingfei Wu, Yao Hu, Enhong Chen:
Linking the Characters: Video-oriented Social Graph Generation via Hierarchical-cumulative GCN. ACM Multimedia 2021: 4716-4724 - [c48]Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Güven, Meng Jiang:
Technical Question Answering across Tasks and Domains. NAACL-HLT (Industry Papers) 2021: 178-186 - [c47]Kai Shen, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhen He, Zhuoye Ding, Yun Xiao, Bo Long:
Learning to Generate Visual Questions with Noisy Supervision. NeurIPS 2021: 11604-11617 - [c46]Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou:
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory. NeurIPS 2021: 30196-30210 - [c45]Lingfei Wu, Yu Chen, Heng Ji, Bang Liu:
Deep Learning on Graphs for Natural Language Processing. SIGIR 2021: 2651-2653 - [c44]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. SANER 2021: 60-71 - [c43]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. SANER 2021: 330-341 - 2020
- [c42]Luyang Huang, Lingfei Wu, Lu Wang:
Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward. ACL 2020: 5094-5107 - [c41]Wenhao Yu, Lingfei Wu, Qingkai Zeng, Shu Tao, Yu Deng, Meng Jiang:
Crossing Variational Autoencoders for Answer Retrieval. ACL 2020: 5635-5641 - [c40]Ying Lin, Heng Ji, Fei Huang, Lingfei Wu:
A Joint Neural Model for Information Extraction with Global Features. ACL 2020: 7999-8009 - [c39]Rajarshi Haldar, Lingfei Wu, Jinjun Xiong, Julia Hockenmaier:
A Multi-Perspective Architecture for Semantic Code Search. ACL 2020: 8563-8568 - [c38]Wenhao Yu, Lingfei Wu, Yu Deng, Ruchi Mahindru, Qingkai Zeng, Sinem Güven, Meng Jiang:
A Technical Question Answering System with Transfer Learning. EMNLP (Demos) 2020: 92-99 - [c37]Shucheng Li, Lingfei Wu, Shiwei Feng, Fangli Xu, Fengyuan Xu, Sheng Zhong:
Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem. EMNLP (Findings) 2020: 2841-2852 - [c36]Hanlu Wu, Tengfei Ma, Lingfei Wu, Tariro Manyumwa, Shouling Ji:
Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning. EMNLP (1) 2020: 3612-3621 - [c35]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation. ICLR 2020 - [c34]Kai Shen, Lingfei Wu, Fangli Xu, Siliang Tang, Jun Xiao, Yueting Zhuang:
Hierarchical Attention Based Spatial-Temporal Graph-to-Sequence Learning for Grounded Video Description. IJCAI 2020: 941-947 - [c33]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension. IJCAI 2020: 1230-1236 - [c32]Hanning Gao, Lingfei Wu, Po Hu, Fangli Xu:
RDF-to-Text Generation with Graph-augmented Structural Neural Encoders. IJCAI 2020: 3030-3036 - [c31]Alexander LeClair, Sakib Haque, Lingfei Wu, Collin McMillan:
Improved Code Summarization via a Graph Neural Network. ICPC 2020: 184-195 - [c30]Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye:
Interpretable Deep Graph Generation with Node-edge Co-disentanglement. KDD 2020: 1697-1707 - [c29]Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma:
Deep Graph Learning: Foundations, Advances and Applications. KDD 2020: 3555-3556 - [c28]Sakib Haque, Alexander LeClair, Lingfei Wu, Collin McMillan:
Improved Automatic Summarization of Subroutines via Attention to File Context. MSR 2020: 300-310 - [c27]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings. NeurIPS 2020 - 2019
- [c26]Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang:
Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting. AAAI 2019: 3638-3646 - [c25]Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng, Liang Zhao:
Multi-stage Deep Classifier Cascades for Open World Recognition. CIKM 2019: 179-188 - [c24]Ziyao Zhang, Liang Ma, Konstantinos Poularakis, Kin K. Leung, Lingfei Wu:
DQ Scheduler: Deep Reinforcement Learning Based Controller Synchronization in Distributed SDN. ICC 2019: 1-7 - [c23]Yuyang Gao, Lingfei Wu, Houman Homayoun, Liang Zhao:
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. ICDM 2019: 1042-1047 - [c22]Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, Lingfei Wu:
Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior. ICDM 2019: 1192-1197 - [c21]Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse:
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. ICML 2019: 1091-1101 - [c20]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Clustering. IJCAI 2019: 2845-2851 - [c19]Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal:
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. KDD 2019: 520-528 - [c18]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. KDD 2019: 1418-1428 - [c17]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. SysML 2019 - [c16]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases. NAACL-HLT (1) 2019: 2913-2923 - [c15]Hongyu Gong, Suma Bhat, Lingfei Wu, Jinjun Xiong, Wen-Mei W. Hwu:
Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus. NAACL-HLT (1) 2019: 3168-3180 - [c14]Zhen Zhang, Yijian Xiang, Lingfei Wu, Bing Xue, Arye Nehorai:
KerGM: Kernelized Graph Matching. NeurIPS 2019: 3330-3341 - [c13]Siyu Huo, Tengfei Ma, Jie Chen, Maria Chang, Lingfei Wu, Michael Witbrock:
Graph Enhanced Cross-Domain Text-to-SQL Generation. TextGraphs@EMNLP 2019: 159-163 - 2018
- [c12]Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney:
Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search. AAAI 2018: 7753-7758 - [c11]Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock:
Random Warping Series: A Random Features Method for Time-Series Embedding. AISTATS 2018: 793-802 - [c10]Zhiqiang Tang, Xi Peng, Shijie Geng, Lingfei Wu, Shaoting Zhang, Dimitris N. Metaxas:
Quantized Densely Connected U-Nets for Efficient Landmark Localization. ECCV (3) 2018: 348-364 - [c9]Kun Xu, Lingfei Wu, Zhiguo Wang, Mo Yu, Liwei Chen, Vadim Sheinin:
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model. EMNLP 2018: 918-924 - [c8]Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, Vadim Sheinin:
SQL-to-Text Generation with Graph-to-Sequence Model. EMNLP 2018: 931-936 - [c7]Lingfei Wu, Ian En-Hsu Yen, Kun Xu, Fangli Xu, Avinash Balakrishnan, Pin-Yu Chen, Pradeep Ravikumar, Michael J. Witbrock:
Word Mover's Embedding: From Word2Vec to Document Embedding. EMNLP 2018: 4524-4534 - [c6]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. KDD 2018: 2506-2515 - 2017
- [c5]Pin-Yu Chen, Lingfei Wu:
Revisiting Spectral Graph Clustering with Generative Community Models. ICDM 2017: 51-60 - 2016
- [c4]Jie Chen, Lingfei Wu, Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran:
Efficient one-vs-one kernel ridge regression for speech recognition. ICASSP 2016: 2454-2458 - [c3]Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan:
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. KDD 2016: 1265-1274 - 2009
- [c2]Lingfei Wu, Max Q.-H. Meng, Zijing Lin, Wu He, Chao Peng, Huawei Liang:
A practical evaluation of radio signal strength for mobile robot localization. ROBIO 2009: 516-522 - 2008
- [c1]Fuqing Wu, Max Q.-H. Meng, Lingfei Wu, Zhuancheng Zhang, Xijun Chen:
The study and improvement of memory management based on SOS. ROBIO 2008: 2040-2044
Parts in Books or Collections
- 2020
- [p1]Lei Yu, Lingfei Wu:
Towards Byzantine-Resilient Federated Learning via Group-Wise Robust Aggregation. Federated Learning 2020: 81-92
Editorship
- 2022
- [e1]Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan:
IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022. IEEE 2022, ISBN 978-1-6654-8045-1 [contents]
Informal and Other Publications
- 2024
- [i100]Xiaoqiang Wang, Bang Liu, Lingfei Wu:
FAC2E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition. CoRR abs/2403.00126 (2024) - [i99]Ruoqi Liu, Lingfei Wu, Ping Zhang:
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs. CoRR abs/2403.03791 (2024) - [i98]Tong Ye, Yangkai Du, Tengfei Ma, Lingfei Wu, Xuhong Zhang, Shouling Ji, Wenhai Wang:
Uncovering LLM-Generated Code: A Zero-Shot Synthetic Code Detector via Code Rewriting. CoRR abs/2405.16133 (2024) - [i97]Tong Ye, Tengfei Ma, Lingfei Wu, Xuhong Zhang, Shouling Ji, Wenhai Wang:
Iterative or Innovative? A Problem-Oriented Perspective for Code Optimization. CoRR abs/2406.11935 (2024) - [i96]Kai Shen, Lingfei Wu, Siliang Tang, Fangli Xu, Bo Long, Yueting Zhuang, Jian Pei:
Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference. CoRR abs/2407.05100 (2024) - 2023
- [i95]Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang:
Pruning Before Training May Improve Generalization, Provably. CoRR abs/2301.00335 (2023) - [i94]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. CoRR abs/2302.11396 (2023) - [i93]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
SkillQG: Learning to Generate Question for Reading Comprehension Assessment. CoRR abs/2305.04737 (2023) - [i92]Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Wenhai Wang, Shouling Ji:
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. CoRR abs/2305.11074 (2023) - [i91]Gangyi Zhang, Chongming Gao, Wenqiang Lei, Xiaojie Guo, Shijun Li, Lingfei Wu, Hongshen Chen, Zhuozhi Ding, Sulong Xu, Xiangnan He:
Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation. CoRR abs/2306.04487 (2023) - [i90]Zefan Wang, Zichuan Liu, Yingying Zhang, Aoxiao Zhong, Lunting Fan, Lingfei Wu, Qingsong Wen:
RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models. CoRR abs/2310.16340 (2023) - [i89]Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Shouling Ji, Wenhai Wang:
CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code. CoRR abs/2310.16853 (2023) - [i88]Yangkai Du, Tengfei Ma, Lingfei Wu, Xuhong Zhang, Shouling Ji:
AdaCCD: Adaptive Semantic Contrasts Discovery based Cross Lingual Adaptation for Code Clone Detection. CoRR abs/2311.07277 (2023) - 2022
- [i87]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. CoRR abs/2201.05540 (2022) - [i86]Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang:
Sequential Search with Off-Policy Reinforcement Learning. CoRR abs/2202.00245 (2022) - [i85]Xiaoqiang Wang, Bang Liu, Fangli Xu, Bo Long, Siliang Tang, Lingfei Wu:
Feeding What You Need by Understanding What You Learned. CoRR abs/2203.02753 (2022) - [i84]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu, Xindong Wu:
Embedding Knowledge for Document Summarization: A Survey. CoRR abs/2204.11190 (2022) - [i83]Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu:
QRelScore: Better Evaluating Generated Questions with Deeper Understanding of Context-aware Relevance. CoRR abs/2204.13921 (2022) - [i82]Di Jin, Cuiying Huo, Jianwu Dang, Peican Zhu, Weixiong Zhang, Witold Pedrycz, Lingfei Wu:
Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning. CoRR abs/2205.00256 (2022) - [i81]Yangkai Du, Tengfei Ma, Lingfei Wu, Yiming Wu, Xuhong Zhang, Bo Long, Shouling Ji:
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning. CoRR abs/2205.10511 (2022) - [i80]Xueying Zhang, Kai Shen, Chi Zhang, Xiaochuan Fan, Yun Xiao, Zhen He, Bo Long, Lingfei Wu:
Scenario-based Multi-product Advertising Copywriting Generation for E-Commerce. CoRR abs/2205.10530 (2022) - [i79]Zhendong Chu, Hongning Wang, Yun Xiao, Bo Long, Lingfei Wu:
Meta Policy Learning for Cold-Start Conversational Recommendation. CoRR abs/2205.11788 (2022) - [i78]Cuiying Huo, Di Jin, Chundong Liang, Dongxiao He, Tie Qiu, Lingfei Wu:
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature. CoRR abs/2205.12784 (2022) - [i77]Dong Chen, Lingfei Wu, Siliang Tang, Xiao Yun, Bo Long, Yueting Zhuang:
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile. CoRR abs/2206.01944 (2022) - [i76]Zhizhi Yu, Di Jin, Jianguo Wei, Ziyang Liu, Yue Shang, Yun Xiao, Jiawei Han, Lingfei Wu:
TeKo: Text-Rich Graph Neural Networks with External Knowledge. CoRR abs/2206.07253 (2022) - [i75]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. CoRR abs/2206.10103 (2022) - [i74]Jiayin Jin, Zeru Zhang, Yang Zhou, Lingfei Wu:
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing. CoRR abs/2206.11423 (2022) - [i73]Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Generation of Product-Image Sequence in E-commerce. CoRR abs/2206.12994 (2022) - [i72]Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang:
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search. CoRR abs/2210.01701 (2022) - [i71]Peng Lin, Yanyan Zou, Lingfei Wu, Mian Ma, Zhuoye Ding, Bo Long:
Automatic Scene-based Topic Channel Construction System for E-Commerce. CoRR abs/2210.02643 (2022) - [i70]Jiajia Li, Feng Tan, Cheng He, Zikai Wang, Haitao Song, Lingfei Wu, Pengwei Hu:
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOps. CoRR abs/2211.07642 (2022) - [i69]Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu:
Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning. CoRR abs/2212.00904 (2022) - [i68]Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu:
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation. CoRR abs/2212.12738 (2022) - 2021
- [i67]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. CoRR abs/2101.02742 (2021) - [i66]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. CoRR abs/2101.03999 (2021) - [i65]Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu:
Relation-aware Graph Attention Model With Adaptive Self-adversarial Training. CoRR abs/2102.07186 (2021) - [i64]April Yi Wang, Dakuo Wang, Jaimie Drozdal, Michael J. Muller, Soya Park, Justin D. Weisz, Xuye Liu, Lingfei Wu, Casey Dugan:
Themisto: Towards Automated Documentation Generation in Computational Notebooks. CoRR abs/2102.12592 (2021) - [i63]Xuye Liu, Dakuo Wang, April Yi Wang, Lingfei Wu:
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks. CoRR abs/2104.01002 (2021) - [i62]Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Shouling Ji:
Constructing Contrastive samples via Summarization for Text Classification with limited annotations. CoRR abs/2104.05094 (2021) - [i61]Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. CoRR abs/2106.06090 (2021) - [i60]Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long:
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation. CoRR abs/2107.03813 (2021) - [i59]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks. CoRR abs/2107.10234 (2021) - [i58]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long:
Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation. CoRR abs/2109.11898 (2021) - [i57]Qi Shen, Lingfei Wu, Yitong Pang, Yiming Zhang, Zhihua Wei, Fangli Xu, Bo Long:
Multi-behavior Graph Contextual Aware Network for Session-based Recommendation. CoRR abs/2109.11903 (2021) - [i56]Hanning Gao, Lingfei Wu, Po Hu, Zhihua Wei, Fangli Xu, Bo Long:
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph. CoRR abs/2111.10541 (2021) - [i55]Hanning Gao, Lingfei Wu, Po Hu, Zhihua Wei, Fangli Xu, Bo Long:
RDF-to-Text Generation with Reinforcement Learning Based Graph-augmented Structural Neural Encoders. CoRR abs/2111.10545 (2021) - [i54]Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent Online Selling Point Extraction for E-Commerce Recommendation. CoRR abs/2112.10613 (2021) - [i53]Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Bo Long, Jian Pei:
Multi-Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation. CoRR abs/2112.11775 (2021) - [i52]Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Automatic Product Copywriting for E-Commerce. CoRR abs/2112.11915 (2021) - [i51]Xiang Ling, Lingfei Wu, Jiangyu Zhang, Zhenqing Qu, Wei Deng, Xiang Chen, Chunming Wu, Shouling Ji, Tianyue Luo, Jingzheng Wu, Yanjun Wu:
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art. CoRR abs/2112.12310 (2021) - 2020
- [i50]Alexander LeClair, Sakib Haque, Lingfei Wu, Collin McMillan:
Improved Code Summarization via a Graph Neural Network. CoRR abs/2004.02843 (2020) - [i49]Sakib Haque, Alexander LeClair, Lingfei Wu, Collin McMillan:
Improved Automatic Summarization of Subroutines via Attention to File Context. CoRR abs/2004.04881 (2020) - [i48]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Toward Subgraph Guided Knowledge Graph Question Generation with Graph Neural Networks. CoRR abs/2004.06015 (2020) - [i47]Shucheng Li, Lingfei Wu, Shiwei Feng, Fangli Xu, Fengyuan Xu, Sheng Zhong:
Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem. CoRR abs/2004.13781 (2020) - [i46]Luyang Huang, Lingfei Wu, Lu Wang:
Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward. CoRR abs/2005.01159 (2020) - [i45]Wenhao Yu, Lingfei Wu, Qingkai Zeng, Yu Deng, Shu Tao, Meng Jiang:
Crossing Variational Autoencoders for Answer Retrieval. CoRR abs/2005.02557 (2020) - [i44]Rajarshi Haldar, Lingfei Wu, Jinjun Xiong, Julia Hockenmaier:
A Multi-Perspective Architecture for Semantic Code Search. CoRR abs/2005.06980 (2020) - [i43]Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye:
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement. CoRR abs/2006.05385 (2020) - [i42]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings. CoRR abs/2006.13009 (2020) - [i41]Xiang Ling, Lingfei Wu, Saizhuo Wang, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Hierarchical Graph Matching Networks for Deep Graph Similarity Learning. CoRR abs/2007.04395 (2020) - [i40]Hanlu Wu, Tengfei Ma, Lingfei Wu, Tariro Manyumwa, Shouling Ji:
Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning. CoRR abs/2010.01781 (2020) - [i39]Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Güven, Meng Jiang:
Technical Question Answering across Tasks and Domains. CoRR abs/2010.09780 (2020) - [i38]Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan, William L. Hamilton:
Stronger Transformers for Neural Multi-Hop Question Generation. CoRR abs/2010.11374 (2020) - [i37]Xiang Ling, Lingfei Wu, Saizhuo Wang, Gaoning Pan, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji:
Deep Graph Matching and Searching for Semantic Code Retrieval. CoRR abs/2010.12908 (2020) - [i36]Hanlu Wu, Tengfei Ma, Lingfei Wu, Shouling Ji:
Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing. CoRR abs/2010.13080 (2020) - 2019
- [i35]Maxwell Crouse, Achille Fokoue, Maria Chang, Pavan Kapanipathi, Ryan Musa, Constantine Nakos, Lingfei Wu, Kenneth D. Forbus, Michael Witbrock:
High-Fidelity Vector Space Models of Structured Data. CoRR abs/1901.02565 (2019) - [i34]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases. CoRR abs/1903.02188 (2019) - [i33]Hongyu Gong, Suma Bhat, Lingfei Wu, Jinjun Xiong, Wen-Mei Hwu:
Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus. CoRR abs/1903.10671 (2019) - [i32]Yao Ma, Suhang Wang, Lingfei Wu, Jiliang Tang:
Attacking Graph Convolutional Networks via Rewiring. CoRR abs/1906.03750 (2019) - [i31]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension. CoRR abs/1908.00059 (2019) - [i30]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation. CoRR abs/1908.04942 (2019) - [i29]Yuyang Gao, Lingfei Wu, Houman Homayoun, Liang Zhao:
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. CoRR abs/1908.08497 (2019) - [i28]Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng, Liang Zhao:
Multi-stage Deep Classifier Cascades for Open World Recognition. CoRR abs/1908.09931 (2019) - [i27]Fangli Xu, Lingfei Wu, K. P. Thai, Carol Hsu, Wei Wang, Richard Jiarui Tong:
MUTLA: A Large-Scale Dataset for Multimodal Teaching and Learning Analytics. CoRR abs/1910.06078 (2019) - [i26]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model. CoRR abs/1910.08832 (2019) - [i25]Maxwell Crouse, Ibrahim Abdelaziz, Cristina Cornelio, Veronika Thost, Lingfei Wu, Kenneth D. Forbus, Achille Fokoue:
Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling. CoRR abs/1911.06904 (2019) - [i24]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. CoRR abs/1911.11119 (2019) - [i23]Zhen Zhang, Yijian Xiang, Lingfei Wu, Bing Xue, Arye Nehorai:
KerGM: Kernelized Graph Matching. CoRR abs/1911.11120 (2019) - [i22]Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal:
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. CoRR abs/1911.11121 (2019) - [i21]Yu Chen, Lingfei Wu, Mohammed J. Zaki:
Deep Iterative and Adaptive Learning for Graph Neural Networks. CoRR abs/1912.07832 (2019) - 2018
- [i20]Lingfei Wu, Ian En-Hsu Yen, Fangli Xu, Pradeep Ravikumar, Michael Witbrock:
D2KE: From Distance to Kernel and Embedding. CoRR abs/1802.04956 (2018) - [i19]Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, Vadim Sheinin:
Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks. CoRR abs/1804.00823 (2018) - [i18]Xiaojie Guo, Lingfei Wu, Liang Zhao:
Deep Graph Translation. CoRR abs/1805.09980 (2018) - [i17]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. CoRR abs/1805.11048 (2018) - [i16]Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse:
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. CoRR abs/1805.11769 (2018) - [i15]Zhiqiang Tang, Xi Peng, Shijie Geng, Lingfei Wu, Shaoting Zhang, Dimitris N. Metaxas:
Quantized Densely Connected U-Nets for Efficient Landmark Localization. CoRR abs/1808.02194 (2018) - [i14]Kun Xu, Lingfei Wu, Zhiguo Wang, Mo Yu, Liwei Chen, Vadim Sheinin:
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model. CoRR abs/1808.07624 (2018) - [i13]Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan:
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. CoRR abs/1809.05247 (2018) - [i12]Kun Xu, Lingfei Wu, Zhiguo Wang, Mo Yu, Liwei Chen, Vadim Sheinin:
SQL-to-Text Generation with Graph-to-Sequence Model. CoRR abs/1809.05255 (2018) - [i11]Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock:
Random Warping Series: A Random Features Method for Time-Series Embedding. CoRR abs/1809.05259 (2018) - [i10]Lingfei Wu, Ian En-Hsu Yen, Kun Xu, Fangli Xu, Avinash Balakrishnan, Pin-Yu Chen, Pradeep Ravikumar, Michael J. Witbrock:
Word Mover's Embedding: From Word2Vec to Document Embedding. CoRR abs/1811.01713 (2018) - [i9]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Attacks and Submodular Optimization with Applications to Text Classification. CoRR abs/1812.00151 (2018) - [i8]Ziyao Zhang, Liang Ma, Konstantinos Poularakis, Kin K. Leung, Lingfei Wu:
DQ Scheduler: Deep Reinforcement Learning Based Controller Synchronization in Distributed SDN. CoRR abs/1812.00852 (2018) - 2017
- [i7]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Analysis. CoRR abs/1702.03584 (2017) - [i6]Pin-Yu Chen, Lingfei Wu:
Revisiting Spectral Graph Clustering with Generative Community Models. CoRR abs/1709.04594 (2017) - [i5]Lingfei Wu, Fei Xue, Andreas Stathopoulos:
TRPL+K: Thick-Restart Preconditioned Lanczos+K Method for Large Symmetric Eigenvalue Problems. CoRR abs/1711.10128 (2017) - 2016
- [i4]Lingfei Wu, Eloy Romero, Andreas Stathopoulos:
PRIMME_SVDS: A High-Performance Preconditioned SVD Solver for Accurate Large-Scale Computations. CoRR abs/1607.01404 (2016) - 2015
- [i3]Lingfei Wu, Kesheng Wu, Alex Sim, Michael Churchill, Jong Youl Choi, Andreas Stathopoulos, Choong-Seock Chang, Scott Klasky:
Towards Real-Time Detection and Tracking of Blob-Filaments in Fusion Plasma Big Data. CoRR abs/1505.03532 (2015) - [i2]Lingfei Wu, Andreas Stathopoulos, Jesse Laeuchli, Vassilis Kalantzis, Efstratios Gallopoulos:
Estimating the Trace of the Matrix Inverse by Interpolating from the Diagonal of an Approximate Inverse. CoRR abs/1507.07227 (2015) - 2014
- [i1]Lingfei Wu, Andreas Stathopoulos:
PRIMME_SVDS: A Preconditioned SVD Solver for Computing Accurately Singular Triplets of Large Matrices based on the PRIMME Eigensolver. CoRR abs/1408.5535 (2014)
Coauthor Index
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