default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKai Shu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j23]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)- [c68]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 - [c67]Canyu Chen, Kai Shu:
Can LLM-Generated Misinformation Be Detected? ICLR 2024 - [c66]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 - [c65]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 - [c64]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]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 - [e3]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] - [i70]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) - [i69]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) - [i68]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) - [i67]Baixiang Huang, Canyu Chen, Kai Shu:
Can Large Language Models Identify Authorship? CoRR abs/2403.08213 (2024) - [i66]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) - [i65]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) - [i64]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) - [i63]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) - [i62]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) - [i61]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) - [i60]Baixiang Huang, Canyu Chen, Kai Shu:
Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges. CoRR abs/2408.08946 (2024) - 2023
- [j22]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]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]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) - [c62]Kai Shu:
Combating Disinformation on Social Media and Its Challenges: A Computational Perspective. AAAI 2023: 15454 - [c61]Canyu Chen, Kai Shu:
PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners. EACL 2023: 562-574 - [c60]Haoran Wang, Kai Shu:
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models. EMNLP (Findings) 2023: 6288-6304 - [c59]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]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]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]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]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 - [i59]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]Baixiang Huang, Bryan Hooi, Kai Shu:
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks. CoRR abs/2304.08640 (2023) - [i57]Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu:
MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection. CoRR abs/2305.10668 (2023) - [i56]SJ Dillon, Yueqing Liang, H. Russell Bernard, Kai Shu:
Investigating Gender Euphoria and Dysphoria on TikTok: Characterization and Comparison. CoRR abs/2305.19552 (2023) - [i55]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) - [i54]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) - [i53]Junwei Yin, Min Gao, Kai Shu, Zehua Zhao, Yinqiu Huang, Jia Wang:
Emulating Reader Behaviors for Fake News Detection. CoRR abs/2306.15231 (2023) - [i52]Aman Rangapur, Haoran Wang, Kai Shu:
Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generation. CoRR abs/2309.08793 (2023) - [i51]Aman Rangapur, Haoran Wang, Kai Shu:
Investigating Online Financial Misinformation and Its Consequences: A Computational Perspective. CoRR abs/2309.12363 (2023) - [i50]Canyu Chen, Kai Shu:
Can LLM-Generated Misinformation Be Detected? CoRR abs/2309.13788 (2023) - [i49]Haoran Wang, Kai Shu:
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models. CoRR abs/2310.05253 (2023) - [i48]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) - [i47]Canyu Chen, Kai Shu:
Combating Misinformation in the Age of LLMs: Opportunities and Challenges. CoRR abs/2311.05656 (2023) - [i46]Yueqing Liang, Lu Cheng, Ali Payani, Kai Shu:
Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models. CoRR abs/2311.09428 (2023) - [i45]Haoran Wang, Kai Shu:
Backdoor Activation Attack: Attack Large Language Models using Activation Steering for Safety-Alignment. CoRR abs/2311.09433 (2023) - 2022
- [j19]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]Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu:
Fair classification via domain adaptation: A dual adversarial learning approach. Frontiers Big Data 5 (2022) - [j17]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]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]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]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]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]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) - [c54]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]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]Kai Shu, Xiandeng He, Lifeng Shi, Nan Chen:
An OTFS Channel Estimation Scheme Based on Efficient Sparse Bayesian Learning. ICCC 2022: 150-155 - [c51]Han Wang, Jayashree Sharma, Shuya Feng, Kai Shu, Yuan Hong:
A Model-Agnostic Approach to Differentially Private Topic Mining. KDD 2022: 1835-1845 - [c50]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]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]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442 - [c47]Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V. Mancenido, Huan Liu:
Domain Adaptive Fake News Detection via Reinforcement Learning. WWW 2022: 3632-3640 - [c46]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 - [i44]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) - [i43]Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V. Mancenido, Huan Liu:
Domain Adaptive Fake News Detection via Reinforcement Learning. CoRR abs/2202.08159 (2022) - [i42]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) - [i41]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) - [i40]Canyu Chen, Kai Shu:
PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners. CoRR abs/2205.09229 (2022) - [i39]Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu:
Joint Adversarial Learning for Cross-domain Fair Classification. CoRR abs/2206.03656 (2022) - [i38]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) - [i37]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) - [i36]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) - [i35]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) - [i34]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
- [j11]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]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]Chenguang Song, Kai Shu, Bin Wu:
Temporally evolving graph neural network for fake news detection. Inf. Process. Manag. 58(6): 102712 (2021) - [c45]Kai Shu, Yichuan Li, Kaize Ding, Huan Liu:
Fact-Enhanced Synthetic News Generation. AAAI 2021: 13825-13833 - [c44]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]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 - [c42]Ahmadreza Mosallanezhad, Kai Shu, Huan Liu:
Generating Topic-Preserving Synthetic News. IEEE BigData 2021: 490-499 - [c41]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 - [c40]Yinqiu Huang, Min Gao, Jia Wang, Kai Shu:
DAFD: Domain Adaptation Framework for Fake News Detection. ICONIP (1) 2021: 305-316 - [c39]Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Causal Understanding of Fake News Dissemination on Social Media. KDD 2021: 148-157 - [c38]Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. KDD 2021: 218-226 - [c37]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]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. SIGIR 2021: 2051-2055 - [c35]Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, Kai Shu:
Mining Dual Emotion for Fake News Detection. WWW 2021: 3465-3476 - [e2]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] - [e1]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] - [i33]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. CoRR abs/2104.12259 (2021) - [i32]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) - [i31]Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. CoRR abs/2106.04716 (2021) - [i30]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]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]Zhao Wang, Kai Shu, Aron Culotta:
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach. CoRR abs/2110.00911 (2021) - 2020
- [j8]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]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]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]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) - [c34]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]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]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]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]Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu:
Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. CIKM (Workshops) 2020 - [c29]Adaku Uchendu, Thai Le, Kai Shu, Dongwon Lee:
Authorship Attribution for Neural Text Generation. EMNLP (1) 2020: 8384-8395 - [c28]Kai Shu, Deepak Mahudeswaran, Suhang Wang, Huan Liu:
Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. ICWSM 2020: 626-637 - [c27]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]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]