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2019
[b1]
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Kai Shu, Huan Liu:
Detecting Fake News on Social Media. Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool Publishers 2019, ISBN 978-3-031-00787-3

Journal Articles

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2024
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Canyu Chen, Kai Shu:
Combating misinformation in the age of LLMs: Opportunities and challenges. AI Mag. 45(3): 354-368 (2024)
[j23]
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Yinqiu Huang, Min Gao, Kai Shu, Chenghua Lin, Jia Wang, Wei Zhou:
EML: Emotion-Aware Meta Learning for Cross-Event False Information Detection. ACM Trans. Knowl. Discov. Data 18(8): 185:1-185:25 (2024)
2023
[j22]
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Jia Wang, Min Gao, Yinqiu Huang, Kai Shu, Hualing Yi:
FinD: Fine-grained discrepancy-based fake news detection enhanced by event abstract generation. Comput. Speech Lang. 78: 101461 (2023)
[j21]
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Yinqiu Huang, Min Gao, Jia Wang, Junwei Yin, Kai Shu, Qilin Fan, Junhao Wen:
Meta-prompt based learning for low-resource false information detection. Inf. Process. Manag. 60(3): 103279 (2023)
[j20]
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Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. IEEE Trans. Knowl. Data Eng. 35(7): 7178-7191 (2023)
2022
[j19]
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Mudassir M. Rashid, Mohammad-Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu, Ali Cinar:
Artificial Intelligence Algorithms for Treatment of Diabetes. Algorithms 15(9): 299 (2022)
[j18]
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Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu:
Fair classification via domain adaptation: A dual adversarial learning approach. Frontiers Big Data 5 (2022)
[j17]
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Tanmoy Chakraborty, Kai Shu, H. Russell Bernard, Huan Liu:
Editorial: Special issue on "Learning to combat online hostile posts in regional languages during emergency situations". Neurocomputing 500: 241-242 (2022)
[j16]
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Ebrahim Bagheri, Huan Liu, Kai Shu, Fattane Zarrinkalam:
Foreword to the special issue on dis/misinformation mining from social media. Inf. Process. Manag. 59(2): 102851 (2022)
[j15]
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Qiang Sheng, Juan Cao, H. Russell Bernard, Kai Shu, Jintao Li, Huan Liu:
Characterizing multi-domain false news and underlying user effects on Chinese Weibo. Inf. Process. Manag. 59(4): 102959 (2022)
[j14]
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Wen Zhang, B. Blair Braden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang:
Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning. Neuroinformatics 20(2): 301-316 (2022)
[j13]
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A. R. Sanaullah, Anupam Das, Anik Das, Muhammad Ashad Kabir, Kai Shu:
Applications of machine learning for COVID-19 misinformation: a systematic review. Soc. Netw. Anal. Min. 12(1): 94 (2022)
[j12]
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Kaize Ding, Kai Shu, Xuan Shan, Jundong Li, Huan Liu:
Cross-Domain Graph Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2406-2415 (2022)
2021
[j11]
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Kai Shu, Susan T. Dumais, Ahmed Hassan Awadallah, Huan Liu:
Detecting Fake News With Weak Social Supervision. IEEE Intell. Syst. 36(4): 96-103 (2021)
[j10]
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Long Zhang, Kai Shu, Keyu Huang, Ruiqiu Zhang:
An Approximation of Label Distribution-Based Ensemble Learning Method for Online Educational Prediction. Int. J. Comput. Commun. Control 16(3) (2021)
[j9]
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Chenguang Song, Kai Shu, Bin Wu:
Temporally evolving graph neural network for fake news detection. Inf. Process. Manag. 58(6): 102712 (2021)
2020
[j8]
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Qun Zhao, Yuelong Zhu, Kai Shu, Dingsheng Wan, Yufeng Yu, Xudong Zhou, Huan Liu:
Joint Spatial and Temporal Modeling for Hydrological Prediction. IEEE Access 8: 78492-78503 (2020)
[j7]
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Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, Huan Liu:
FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media. Big Data 8(3): 171-188 (2020)
[j6]
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Ping Luo, Kai Shu, Junjie Wu, Li Wan, Yong Tan:
Exploring Correlation Network for Cheating Detection. ACM Trans. Intell. Syst. Technol. 11(1): 12:1-12:23 (2020)
[j5]
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Kai Shu, Amrita Bhattacharjee, Faisal Alatawi, Tahora H. Nazer, Kaize Ding, Mansooreh Karami, Huan Liu:
Combating disinformation in a social media age. WIREs Data Mining Knowl. Discov. 10(6) (2020)
2019
[j4]
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Kai Shu, Deepak Mahudeswaran, Huanyu Liu:
FakeNewsTracker: a tool for fake news collection, detection, and visualization. Comput. Math. Organ. Theory 25(1): 60-71 (2019)
[j3]
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Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Towards privacy preserving social recommendation under personalized privacy settings. World Wide Web 22(6): 2853-2881 (2019)
2017
[j2]
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Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, Huan Liu:
Fake News Detection on Social Media: A Data Mining Perspective. SIGKDD Explor. 19(1): 22-36 (2017)
2016
[j1]
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Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, Huan Liu:
User Identity Linkage across Online Social Networks: A Review. SIGKDD Explor. 18(2): 5-17 (2016)

Conference and Workshop Papers

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2024
[c73]
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Haoran Wang, Kai Shu:
Trojan Activation Attack: Red-Teaming Large Language Models using Steering Vectors for Safety-Alignment. CIKM 2024: 2347-2357
[c72]
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Alimohammad Beigi, Zhen Tan, Nivedh Mudiam, Canyu Chen, Kai Shu, Huan Liu:
Model Attribution in LLM-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning. DSAA 2024: 1-10
[c71]
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Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu:
MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection. DSAA 2024: 1-10
[c70]
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Baixiang Huang, Canyu Chen, Kai Shu:
Can Large Language Models Identify Authorship? EMNLP (Findings) 2024: 445-460
[c69]
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Junwei Yin, Min Gao, Kai Shu, Jia Wang, Yinqiu Huang, Wei Zhou:
Fine-Grained Discrepancy Contrastive Learning for Robust Fake News Detection. ICASSP 2024: 12541-12545
[c68]
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Canyu Chen, Kai Shu:
Can LLM-Generated Misinformation Be Detected? ICLR 2024
[c67]
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Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024
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Jianfei Xiao, Yancan Chen, Yimin Ou, Hanyi Yu, Kai Shu, Yiyong Xiao:
Baichuan2-Sum: Instruction Finetune Baichuan2-7B Model for Dialogue Summarization. IJCNN 2024: 1-8
[c65]
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Yiyong Xiao, Kai Shu, Haoyi Zhang, Baohua Yin, Wai Seng Cheang, Haoyang Wang, Jiechao Gao:
EGGesture: Entropy-Guided Vector Quantized Variational AutoEncoder for Co-Speech Gesture Generation. ACM Multimedia 2024: 6113-6122
[c64]
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Xiongxiao Xu, Kevin A. Brown, Tanwi Mallick, Xin Wang, Elkin Cruz-Camacho, Robert B. Ross, Christopher D. Carothers, Zhiling Lan, Kai Shu:
Surrogate Modeling for HPC Application Iteration Times Forecasting with Network Features. SIGSIM-PADS 2024: 93-97
[c63]
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Yue Huang, Kai Shu, Philip S. Yu, Lichao Sun:
From Creation to Clarification: ChatGPT's Journey Through the Fake News Quagmire. WWW (Companion Volume) 2024: 513-516
2023
[c62]
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Kai Shu:
Combating Disinformation on Social Media and Its Challenges: A Computational Perspective. AAAI 2023: 15454
[c61]
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Canyu Chen, Kai Shu:
PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners. EACL 2023: 562-574
[c60]
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Haoran Wang, Kai Shu:
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models. EMNLP (Findings) 2023: 6288-6304
[c59]
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Baixiang Huang, Bryan Hooi, Kai Shu:
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks. SIGSPATIAL/GIS 2023: 105:1-105:4
[c58]
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Hao Liao, Jiahao Peng, Zhanyi Huang, Wei Zhang, Guanghua Li, Kai Shu, Xing Xie:
MUSER: A MUlti-Step Evidence Retrieval Enhancement Framework for Fake News Detection. KDD 2023: 4461-4472
[c57]
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Elkin Cruz-Camacho, Kevin A. Brown, Xin Wang, Xiongxiao Xu, Kai Shu, Zhiling Lan, Robert B. Ross, Christopher D. Carothers:
Hybrid PDES Simulation of HPC Networks Using Zombie Packets. SIGSIM-PADS 2023: 128-132
[c56]
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Xiongxiao Xu, Xin Wang, Elkin Cruz-Camacho, Christopher D. Carothers, Kevin A. Brown, Robert B. Ross, Zhiling Lan, Kai Shu:
Machine Learning for Interconnect Network Traffic Forecasting: Investigation and Exploitation. SIGSIM-PADS 2023: 133-137
[c55]
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Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. WWW 2023: 3978-3986
2022
[c54]
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Miyoung Chong, Chirag Shah, Kai Shu, Jiangen He, Loni Hagen:
Delving into Data Science Methods in Response to the COVID -19 Infodemic. ASIST 2022: 555-558
[c53]
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Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. IEEE Big Data 2022: 596-605
[c52]
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Kai Shu, Xiandeng He, Lifeng Shi, Nan Chen:
An OTFS Channel Estimation Scheme Based on Efficient Sparse Bayesian Learning. ICCC 2022: 150-155
[c51]
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Han Wang, Jayashree Sharma, Shuya Feng, Kai Shu, Yuan Hong:
A Model-Agnostic Approach to Differentially Private Topic Mining. KDD 2022: 1835-1845
[c50]
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  - conf/naacl/ZhengKSA22
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Guoqing Zheng, Giannis Karamanolakis, Kai Shu, Ahmed Hassan Awadallah:
WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding. NAACL-HLT 2022: 873-899
[c49]
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Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS 2022
[c48]
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Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442
[c47]
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Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V. Mancenido, Huan Liu:
Domain Adaptive Fake News Detection via Reinforcement Learning. WWW 2022: 3632-3640
[c46]
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Xinyi Zhou, Kai Shu, Vir V. Phoha, Huan Liu, Reza Zafarani:
"This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders. WWW 2022: 3685-3694
2021
[c45]
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Kai Shu, Yichuan Li, Kaize Ding, Huan Liu:
Fact-Enhanced Synthetic News Generation. AAAI 2021: 13825-13833
[c44]
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Miyoung Chong, Thomas J. Froehlich, Kai Shu:
Racial Attacks during the COVID -19 Pandemic: Politicizing an Epidemic Crisis on Longstanding Racism and Misinformation, Disinformation, and Misconception. ASIST 2021: 573-576
[c43]
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Michele Coscia, Alfredo Cuzzocrea, Kai Shu:
Advances in Social Network Analysis and Mining in the Big Data Era: Overview of the IEEE/ACM ASONAM 2021 International Conference. ASONAM 2021: xi-xii
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Ahmadreza Mosallanezhad, Kai Shu, Huan Liu:
Generating Topic-Preserving Synthetic News. IEEE BigData 2021: 490-499
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Yichuan Li, Kyumin Lee, Nima Kordzadeh, Brenton D. Faber, Cameron Fiddes, Elaine Chen, Kai Shu:
Multi-Source Domain Adaptation with Weak Supervision for Early Fake News Detection. IEEE BigData 2021: 668-676
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Yinqiu Huang, Min Gao, Jia Wang, Kai Shu:
DAFD: Domain Adaptation Framework for Fake News Detection. ICONIP (1) 2021: 305-316
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Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Causal Understanding of Fake News Dissemination on Social Media. KDD 2021: 148-157
[c38]
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Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. KDD 2021: 218-226
[c37]
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Aude Hofleitner, Meng Jiang, Srijan Kumar, Neil Shah, Kai Shu:
The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web. KDD 2021: 4129-4130
[c36]
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Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. SIGIR 2021: 2051-2055
[c35]
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Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, Kai Shu:
Mining Dual Emotion for Fake News Detection. WWW 2021: 3465-3476
2020
[c34]
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Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu:
Toward A Multilingual and Multimodal Data Repository for COVID-19 Disinformation. IEEE BigData 2020: 4325-4330
[c33]
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Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah L. Hall, Huan Liu:
Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model. CIKM 2020: 185-194
[c32]
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Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu:
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CIKM 2020: 295-304
[c31]
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Ebrahim Bagheri, Huan Liu, Kai Shu, Fattane Zarrinkalam:
The 5th International Workshop on Mining Actionable Insights from Social Networks (MAISoN 2020): Special Edition on Dis/Misinformation Mining from Social media. CIKM 2020: 3527-3528
[c30]
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Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu:
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. CIKM (Workshops) 2020
[c29]
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Adaku Uchendu, Thai Le, Kai Shu, Dongwon Lee:
Authorship Attribution for Neural Text Generation. EMNLP (1) 2020: 8384-8395
[c28]
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Kai Shu, Deepak Mahudeswaran, Suhang Wang, Huan Liu:
Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. ICWSM 2020: 626-637
[c27]
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Qianru Wang, Bin Guo, Yi Ouyang, Kai Shu, Zhiwen Yu, Huan Liu:
Spatial Community-Informed Evolving Graphs for Demand Prediction. ECML/PKDD (5) 2020: 440-456
[c26]
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Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott W. Ruston, Huan Liu:
Early Detection of Fake News with Multi-source Weak Social Supervision. ECML/PKDD (3) 2020: 650-666
[c25]
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Kai Shu, Subhabrata Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah, Milad Shokouhi, Susan T. Dumais:
Learning with Weak Supervision for Email Intent Detection. SIGIR 2020: 1051-1060
[c24]
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Kai Shu, Liangda Li, Suhang Wang, Yunhong Zhou, Huan Liu:
Joint Local and Global Sequence Modeling in Temporal Correlation Networks for Trending Topic Detection. WebSci 2020: 335-344
2019
[c23]
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Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, Huan Liu:
Unsupervised Fake News Detection on Social Media: A Generative Approach. AAAI 2019: 5644-5651
[c22]
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Thai Le, Kai Shu, Maria D. Molina, Dongwon Lee, S. Shyam Sundar, Huan Liu:
5 sources of clickbaits you should know!: using synthetic clickbaits to improve prediction and distinguish between bot-generated and human-written headlines. ASONAM 2019: 33-40
[c21]
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Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, Huan Liu:
The role of user profiles for fake news detection. ASONAM 2019: 436-439
[c20]
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Limeng Cui, Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu:
dEFEND: A System for Explainable Fake News Detection. CIKM 2019: 2961-2964
[c19]
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Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
Privacy Preserving Text Representation Learning. HT 2019: 275-276
[c18]
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Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, Huan Liu:
dEFEND: Explainable Fake News Detection. KDD 2019: 395-405
[c17]
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Reza Zafarani, Xinyi Zhou, Kai Shu, Huan Liu:
Fake News Research: Theories, Detection Strategies, and Open Problems. KDD 2019: 3207-3208
[c16]
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Jayashree Subramanian, Varun Sridharan, Kai Shu, Huan Liu:
Exploiting Emojis for Sarcasm Detection. SBP-BRiMS 2019: 70-80
[c15]
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Kai Shu, Suhang Wang, Huan Liu:
Beyond News Contents: The Role of Social Context for Fake News Detection. WSDM 2019: 312-320
[c14]
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Vineeth Rakesh, Suhang Wang, Kai Shu, Huan Liu:
Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items. WSDM 2019: 438-446
[c13]
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Xinyi Zhou, Reza Zafarani, Kai Shu, Huan Liu:
Fake News: Fundamental Theories, Detection Strategies and Challenges. WSDM 2019: 836-837
2018
[c12]
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Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Personalized Privacy-Preserving Social Recommendation. AAAI 2018: 3796-3803
[c11]
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Kai Shu, Suhang Wang, Huan Liu, Jiliang Tang, Yi Chang, Ping Luo:
Exploiting User Actions for App Recommendations. ASONAM 2018: 139-142
[c10]
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Ghazaleh Beigi, Kai Shu, Yanchao Zhang, Huan Liu:
Securing Social Media User Data: An Adversarial Approach. HT 2018: 165-173
[c9]
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Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, Huan Liu:
Deep Headline Generation for Clickbait Detection. ICDM 2018: 467-476
[c8]
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Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang:
Multimodal Fusion of Brain Networks with Longitudinal Couplings. MICCAI (3) 2018: 3-11
[c7]
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Kai Shu, Suhang Wang, Huan Liu:
Understanding User Profiles on Social Media for Fake News Detection. MIPR 2018: 430-435
[c6]
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Kai Shu, Amy Sliva, Justin Sampson, Huan Liu:
Understanding Cyber Attack Behaviors with Sentiment Information on Social Media. SBP-BRiMS 2018: 377-388
[c5]
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Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu:
CrossFire: Cross Media Joint Friend and Item Recommendations. WSDM 2018: 522-530
2017
[c4]
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Kai Shu, Yanteng Wang, Guanghui Zhao:
Beamforming with Enhanced CNN Network. ICNCC 2017: 197-201
[c3]
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Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, Huan Liu:
What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation. WWW 2017: 391-400
2016
[c2]
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Ling Jian, Jundong Li, Kai Shu, Huan Liu:
Multi-Label Informed Feature Selection. IJCAI 2016: 1627-1633
2014
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Kai Shu, Ping Luo, Wan Li, Peifeng Yin, Linpeng Tang:
Deal or deceit: detecting cheating in distribution channels. CIKM 2014: 1419-1428

Editorship

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2024
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Sascha Hunold, Biwei Xie, Kai Shu:
Benchmarking, Measuring, and Optimizing - 15th BenchCouncil International Symposium, Bench 2023, Sanya, China, December 3-5, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14521, Springer 2024, ISBN 978-981-97-0315-9 [contents]
2021
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Tanmoy Chakraborty, Kai Shu, H. Russell Bernard, Huan Liu, Md. Shad Akhtar:
Combating Online Hostile Posts in Regional Languages during Emergency Situation - First International Workshop, CONSTRAINT 2021, Collocated with AAAI 2021, Virtual Event, February 8, 2021, Revised Selected Papers. Communications in Computer and Information Science 1402, Springer 2021, ISBN 978-3-030-73695-8 [contents]
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Michele Coscia, Alfredo Cuzzocrea, Kai Shu, Ralf Klamma, Sharyn O'Halloran, Jon G. Rokne:
ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8 - 11, 2021. ACM 2021, ISBN 978-1-4503-9128-3 [contents]

Informal and Other Publications

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2024
[i73]
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Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024)
[i72]
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Yunpeng Xiao, Kyrie Zhixuan Zhou, Yueqing Liang, Kai Shu:
Understanding the concerns and choices of public when using large language models for healthcare. CoRR abs/2401.09090 (2024)
[i71]
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Chengxing Xie, Canyu Chen, Feiran Jia, Ziyu Ye, Kai Shu, Adel Bibi, Ziniu Hu, Philip Torr, Bernard Ghanem, Guohao Li:
Can Large Language Model Agents Simulate Human Trust Behaviors? CoRR abs/2402.04559 (2024)
[i70]
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Baixiang Huang, Canyu Chen, Kai Shu:
Can Large Language Models Identify Authorship? CoRR abs/2403.08213 (2024)
[i69]
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Guanghua Li, Wensheng Lu, Wei Zhang, Defu Lian, Kezhong Lu, Rui Mao, Kai Shu, Hao Liao:
Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors. CoRR abs/2403.09747 (2024)
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Xiongxiao Xu, Yueqing Liang, Baixiang Huang, Zhiling Lan, Kai Shu:
Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting. CoRR abs/2404.14757 (2024)
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Qin Yang, Meisam Mohammady, Han Wang, Ali Payani, Ashish Kundu, Kai Shu, Yan Yan, Yuan Hong:
LMO-DP: Optimizing the Randomization Mechanism for Differentially Private Fine-Tuning (Large) Language Models. CoRR abs/2405.18776 (2024)
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Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu:
Taxonomy-Guided Zero-Shot Recommendations with LLMs. CoRR abs/2406.14043 (2024)
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Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu:
Can Editing LLMs Inject Harm? CoRR abs/2407.20224 (2024)
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Alimohammad Beigi, Zhen Tan, Nivedh Mudiam, Canyu Chen, Kai Shu, Huan Liu:
Model Attribution in Machine-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning. CoRR abs/2407.21264 (2024)
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Baixiang Huang, Canyu Chen, Kai Shu:
Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges. CoRR abs/2408.08946 (2024)
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Kai Shu, Yuzhuo Jia, Ziyang Zhang, Jiechao Gao:
FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes. CoRR abs/2409.03947 (2024)
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Xiongxiao Xu, Solomon Abera Bekele, Brice Videau, Kai Shu:
Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach. CoRR abs/2410.11855 (2024)
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Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, Kai Shu:
Can Knowledge Editing Really Correct Hallucinations? CoRR abs/2410.16251 (2024)
2023
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Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. CoRR abs/2302.07363 (2023)
[i58]
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Baixiang Huang, Bryan Hooi, Kai Shu:
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks. CoRR abs/2304.08640 (2023)
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Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu:
MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection. CoRR abs/2305.10668 (2023)
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SJ Dillon, Yueqing Liang, H. Russell Bernard, Kai Shu:
Investigating Gender Euphoria and Dysphoria on TikTok: Characterization and Comparison. CoRR abs/2305.19552 (2023)
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Kai Shu, Yuchang Zhao, Le Wu, Aiping Liu, Ruobing Qian, Xun Chen:
Data Augmentation for Seizure Prediction with Generative Diffusion Model. CoRR abs/2306.08256 (2023)
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Hao Liao, Jiaohao Peng, Zhanyi Huang, Wei Zhang, Guanghua Li, Kai Shu, Xing Xie:
MUSER: A MUlti-Step Evidence Retrieval Enhancement Framework for Fake News Detection. CoRR abs/2306.13450 (2023)
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Junwei Yin, Min Gao, Kai Shu, Zehua Zhao, Yinqiu Huang, Jia Wang:
Emulating Reader Behaviors for Fake News Detection. CoRR abs/2306.15231 (2023)
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Aman Rangapur, Haoran Wang, Kai Shu:
Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generation. CoRR abs/2309.08793 (2023)
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Aman Rangapur, Haoran Wang, Kai Shu:
Investigating Online Financial Misinformation and Its Consequences: A Computational Perspective. CoRR abs/2309.12363 (2023)
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Canyu Chen, Kai Shu:
Can LLM-Generated Misinformation Be Detected? CoRR abs/2309.13788 (2023)
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Haoran Wang, Kai Shu:
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models. CoRR abs/2310.05253 (2023)
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Qiong Nan, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Guang Yang, Jintao Li, Kai Shu:
Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting. CoRR abs/2310.10429 (2023)
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Canyu Chen, Kai Shu:
Combating Misinformation in the Age of LLMs: Opportunities and Challenges. CoRR abs/2311.05656 (2023)
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Yueqing Liang, Lu Cheng, Ali Payani, Kai Shu:
Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models. CoRR abs/2311.09428 (2023)
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Haoran Wang, Kai Shu:
Backdoor Activation Attack: Attack Large Language Models using Activation Steering for Safety-Alignment. CoRR abs/2311.09433 (2023)
2022
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Xinyi Zhou, Kai Shu, Vir V. Phoha, Huan Liu, Reza Zafarani:
"This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders. CoRR abs/2202.04752 (2022)
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Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V. Mancenido, Huan Liu:
Domain Adaptive Fake News Detection via Reinforcement Learning. CoRR abs/2202.08159 (2022)
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  - journals/corr/abs-2204-12095
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Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. CoRR abs/2204.12095 (2022)
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Qiang Sheng, Juan Cao, H. Russell Bernard, Kai Shu, Jintao Li, Huan Liu:
Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo. CoRR abs/2205.03068 (2022)
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  - journals/corr/abs-2205-09229
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Canyu Chen, Kai Shu:
PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners. CoRR abs/2205.09229 (2022)
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Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu:
Joint Adversarial Learning for Cross-domain Fair Classification. CoRR abs/2206.03656 (2022)
[i38]
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  - journals/corr/abs-2206-10071
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Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022)
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Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. CoRR abs/2206.12808 (2022)
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  - journals/corr/abs-2207-08336
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Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Yuan Hong, Kai Shu:
On Fair Classification with Mostly Private Sensitive Attributes. CoRR abs/2207.08336 (2022)
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Canyu Chen, Haoran Wang, Matthew Shapiro, Yunyu Xiao, Fei Wang, Kai Shu:
Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues. CoRR abs/2211.05289 (2022)
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  - journals/corr/abs-2212-12621
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Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. CoRR abs/2212.12621 (2022)
2021
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  - journals/corr/abs-2104-12259
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Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. CoRR abs/2104.12259 (2021)
[i32]
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Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. CoRR abs/2104.14537 (2021)
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  - journals/corr/abs-2106-04716
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Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. CoRR abs/2106.04716 (2021)
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Guoqing Zheng, Giannis Karamanolakis, Kai Shu, Ahmed Hassan Awadallah:
WALNUT: A Benchmark on Weakly Supervised Learning for Natural Language Understanding. CoRR abs/2108.12603 (2021)
[i29]
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  - journals/corr/abs-2110-00737
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A. R. Sana Ullah, Anupam Das, Anik Das, Muhammad Ashad Kabir, Kai Shu:
A Survey of COVID-19 Misinformation: Datasets, Detection Techniques and Open Issues. CoRR abs/2110.00737 (2021)
[i28]
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Zhao Wang, Kai Shu, Aron Culotta:
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach. CoRR abs/2110.00911 (2021)
2020
[i27]
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  - journals/corr/abs-2001-00623
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Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu:
Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements. CoRR abs/2001.00623 (2020)
[i26]
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Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott W. Ruston, Huan Liu:
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News. CoRR abs/2004.01732 (2020)
[i25]
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Kai Shu, Subhabrata Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah, Milad Shokouhi, Susan T. Dumais:
Learning with Weak Supervision for Email Intent Detection. CoRR abs/2005.13084 (2020)
[i24]
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Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu:
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. CoRR abs/2005.13691 (2020)
[i23]
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Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu:
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CoRR abs/2006.12739 (2020)
[i22]
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Kai Shu, Amrita Bhattacharjee, Faisal Alatawi, Tahora H. Nazer, Kaize Ding, Mansooreh Karami, Huan Liu:
Combating Disinformation in a Social Media Age. CoRR abs/2007.07388 (2020)
[i21]
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  - journals/corr/abs-2008-02642
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Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah L. Hall, Huan Liu:
Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model. CoRR abs/2008.02642 (2020)
[i20]
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Amrita Bhattacharjee, Kai Shu, Min Gao, Huan Liu:
Disinformation in the Online Information Ecosystem: Detection, Mitigation and Challenges. CoRR abs/2010.09113 (2020)
[i19]
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  - journals/corr/abs-2010-10580
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Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Towards Causal Understanding of Fake News Dissemination. CoRR abs/2010.10580 (2020)
[i18]
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  - journals/corr/abs-2010-16324
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Ahmadreza Mosallanezhad, Kai Shu, Huan Liu:
Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach. CoRR abs/2010.16324 (2020)
[i17]
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  - journals/corr/abs-2011-01579
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Hao Liao, Qi-Xin Liu, Kai Shu, Xing Xie:
Incorporating User-Comment Graph for Fake News Detection. CoRR abs/2011.01579 (2020)
[i16]
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  - journals/corr/abs-2011-04088
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Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu:
MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation. CoRR abs/2011.04088 (2020)
[i15]
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  - journals/corr/abs-2012-04778
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Kai Shu, Yichuan Li, Kaize Ding, Huan Liu:
Fact-Enhanced Synthetic News Generation. CoRR abs/2012.04778 (2020)
2019
[i14]
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  - journals/corr/abs-1903-01728
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Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, Kai Shu:
Mining Dual Emotion for Fake News Detection. CoRR abs/1903.01728 (2019)
[i13]
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  - journals/corr/abs-1903-02174
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Wen Zhang, Kai Shu, Huan Liu, Yalin Wang:
Graph Neural Networks for User Identity Linkage. CoRR abs/1903.02174 (2019)
[i12]
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  - journals/corr/abs-1903-09196
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Kai Shu, Deepak Mahudeswaran, Suhang Wang, Huan Liu:
Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. CoRR abs/1903.09196 (2019)
[i11]
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  - journals/corr/abs-1904-13355
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Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, Huan Liu:
The Role of User Profile for Fake News Detection. CoRR abs/1904.13355 (2019)
[i10]
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  - journals/corr/abs-1905-03035
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Yufeng Yu, Yuelong Zhu, Dingsheng Wan, Qun Zhao, Kai Shu, Huan Liu:
Applications of Social Media in Hydroinformatics: A Survey. CoRR abs/1905.03035 (2019)
[i9]
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  - journals/corr/abs-1907-03189
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Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
I Am Not What I Write: Privacy Preserving Text Representation Learning. CoRR abs/1907.03189 (2019)
[i8]
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  - journals/corr/abs-1910-11430
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Kai Shu, Ahmed Hassan Awadallah, Susan T. Dumais, Huan Liu:
Detecting Fake News with Weak Social Supervision. CoRR abs/1910.11430 (2019)
[i7]
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  - journals/corr/abs-1910-12417
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Raha Moraffah, Kai Shu, Adrienne Raglin, Huan Liu:
Deep causal representation learning for unsupervised domain adaptation. CoRR abs/1910.12417 (2019)
2018
[i6]
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  - journals/corr/abs-1804-10233
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Kai Shu, H. Russell Bernard, Huan Liu:
Studying Fake News via Network Analysis: Detection and Mitigation. CoRR abs/1804.10233 (2018)
[i5]
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  - journals/corr/abs-1805-00519
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Ghazaleh Beigi, Kai Shu, Yanchao Zhang, Huan Liu:
Securing Social Media User Data - An Adversarial Approach. CoRR abs/1805.00519 (2018)
[i4]
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  - journals/corr/abs-1809-01286
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Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, Huan Liu:
FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media. CoRR abs/1809.01286 (2018)
2017
[i3]
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  - journals/corr/abs-1708-01967
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Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, Huan Liu:
Fake News Detection on Social Media: A Data Mining Perspective. CoRR abs/1708.01967 (2017)
[i2]
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  - journals/corr/abs-1709-04969
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Fred Morstatter, Kai Shu, Suhang Wang, Huan Liu:
Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications. CoRR abs/1709.04969 (2017)
[i1]
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  - journals/corr/abs-1712-07709
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Kai Shu, Suhang Wang, Huan Liu:
Exploiting Tri-Relationship for Fake News Detection. CoRR abs/1712.07709 (2017)

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