|
I am a fourth-year PhD student in Computer Science at the University of Chinese Academy of Sciences (UCAS). I am doing research at the Media Synthesis and Forensics Lab (formerly known as Multimedia Computing Group), Institute of Computing Technology, CAS. My advisor is Professor Juan Cao. My research interests include:
Contact: shengqiang18z AT ict dot ac dot cn Currículum Vitae / GitHub / Google Scholar / ResearchGate / ORCID / DBLP |
|
|
| 08/2022 | One co-authored paper got accepted by COLING 2022. |
| 07/2022 | Invited to serve as a PC Member for AAAI 2023. |
| 07/2022 | Recognized as the Outstanding Reviewer (81/2824) by NAACL 2022 Program Committee. |
| 06/2022 | Invited to serve as a Reviewer for EMNLP 2022. |
| 06/2022 | One co-authored paper got accepted by IEEE TKDE. |
| 04/2022 | Will give a spotlight presentation on our ACL 2022 work at the AIS 2022. |
| 04/2022 | One first-authored paper got accepted by Information Processing and Management. |
| 04/2022 | Will give talks on our ACL 2022 work at the BUAFAI 2022 and AI TIME Live. |
| 04/2022 | One co-authored paper got accepted by SIGIR 2022. |
| 02/2022 | One first-authored paper got accepted by ACL 2022. |
| 12/2021 | One co-authored paper got accepted by AAAI 2022. |
| 10/2021 | Invited to serve as a Reviewer for ACL Rolling Review. |
|
|
|
|
|
Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, Jintao Li Proceedings of the 29th InternationalConference on Computational Linguistics (COLING 2022) Preprint TL;DR: We propose a domain- and instance-level transfer framework for detecting fake news of target domains. |
|
Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang and Fuzhen Zhuang IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 Early Access Version / Preprint / Code / Chinese Blog TL;DR: We tackle the issue of domain shift and domain labeling incompleteness for simultaneously modeling multi-domain fake news via multi-view encoding and memory bank mechanism. |
|
Qiang Sheng, Juan Cao, H. Russell Bernard, Kai Shu, Jintao Li, and Huan Liu Information Processing and Management (IP&M), 2022 Preprint / Paper / Code / Dataset / Chinese Brief TL;DR: Based on the largest false news dataset on Chinese Weibo (44k+), we characterize the spread of false news in nine domains and analyze the underlying user effects. |
|
Yongchun Zhu, Qiang Sheng, Juan Cao, Shuokai Li, Danding Wang, and Fuzhen Zhuang Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022) (Acceptance Rate:165/667=24.7%) Preprint / Paper / Chinese Blog TL;DR: We reveal the entity bias in fake news detection datasets and propose a causal framework to mitigate such bias for better generalization to future data. |
|
Qiang Sheng, Juan Cao, Xueyao Zhang, Rundong Li, Danding Wang, and Yongchun Zhu Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) Preprint / Paper / Poster / Code / Dataset / Chinese Video / Chinese Blog / English Blog TL;DR: For the first time, we propose to perceive signals from the news environment for fake news detection. |
|
Guang Yang, Juan Cao, Qiang Sheng, Peng Qi, Xirong Li, and Jintao Li Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI 2022) (Acceptance Rate:1349/9020=15.0%) Preprint / Paper / English Video TL;DR: We propose a GCN-based method to dynamically find out crucial privacy-indicative regions for privacy-leaking image detection. |
|
|
Peng Qi, Juan Cao, Xirong Li, Huan Liu, Qiang Sheng, Xiaoyue Mi, Qin He, Yongbiao Lv, Chenyang Guo, and Yingchao Yu Proceedings of the 29th ACM International Conference on Multimedia (MM 2021) Preprint / Paper / Chinese Blog 1/ 2 TL;DR: We point out three valuable text-image correlations in multimodal fake news and propose an entity-enhanced fusion framework for cross-modal correlation modeling in fake news detection. |
|
Qiang Sheng*, Xueyao Zhang*, Juan Cao, and Lei Zhong (*:Equal Contribution) Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021) (Acceptance Rate:271/1251=21.7%) Preprint / Paper / Poster / Code / Datasets / Chinese Blog 1/ 2/ 3 TL;DR: We propose a graph-based model preference learning framework to separately handle the pattern and fact indicators in fake news detection. |
|
Qiang Sheng, Juan Cao, Xueyao Zhang, Xirong Li, and Lei Zhong Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) (Acceptance Rate:571/2327=24.5%) Preprint / Paper / Poster / Code / Chinese Dataset / Chinese Blog 1/ 2/ 3 TL;DR: We detect previously fact-checked claims by matching them against the key sentences in fact-checking articles. |
|
Peng Qi, Juan Cao, and Qiang Sheng Journal of Computer Reasearch and Development, 2021 Paper TL;DR: We focus on the role of explicit semantics for fake news detection via visual semantic extraction and knowledge-guided multi-modal semantic interaction. |
|
Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, and Kai Shu Proceedings of the 30th Web Conference (WWW 2021) (Acceptance Rate:357/1736=20.6%) Preprint / Paper / Code / Chinese Video TL;DR: We leverage both publisher emotion and social emotion for fake news detection. |
|
|
Lei Zhong, Juan Cao, Qiang Sheng, Junbo Guo, and Ziang Wang Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020) (Acceptance Rate:571/2244=25.4%) Paper / Chinese Dataset TL;DR: We propose a GCN-based method for post-level controversy detection. Also, we release the first Chinese dataset for this task. |
|
Juan Cao, Qiang Sheng, and Peng Qi Communications of the China Computer Federation, March 2020 Webpage Version / Chinese Blog TL;DR: We review the recent advances of detecting fake news and disinformation and propose potential directions. |
|
Juan Cao, Peng Qi, Qiang Sheng, Tianyun Yang, Junbo Guo, and Jintao Li Disinformation, Misinformation, and Fake News in Social Media: Emerging Research Challenges and Opportunities, Lecture Notes in Social Network (LNSN) Preprint / Springer Link TL;DR: A survey chapter that focuses on the visual information for fake news detection. |
|
|
| 2022/5/14 | AIS 2022 (NLU Session) (Event / Session Video) |
| 2022/4/24 | BUAFAI 2022 (NLP & Speech Forum) (WeChat Article / Chinese Video) |
| 2022/4/20 | AI TIME Live (WeChat Article / Chinese Video / Chinese Blog) |
|
|
| 2020/2021 Spring | Teaching Assistant, 081203M05008H: Multimedia Technology, UCAS |
|
|
| Reviewer/PC Member |
AAAI 2023
EMNLP 2022 NAACL 2022 (Recognized as the Outstanding Reviewer) ACL 2022 ACL Rolling Review (Nov. 2021~) AAAI 2022 EMNLP 2021 ACM CSCW 2021 (Recognized for Excellent Reviewing) Information Processing and Management Multimedia Systems |
| Student Volunteer | IEEE ICDM 2019 |
|
|
| 2018- |
Ph.D in Computer Science and Technology (Candidate)
University of Chinese Academy of Sciences (Cultivation Unit: Institute of Computing Technology, CAS) |
| 2014-2018 |
B. Eng in Communication Engineering
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications |
| 2011-2014 | Weifang No.1 Middle School |
|
|
| 2022 | Pacemaker to Merit Student of UCAS, UCAS |
| 2022 | E Fund Scholarship, Guangdong E Fund Education Foundation & ICT, CAS |
| 2019, 2020 | Merit Student, University of Chinese Academy of Sciences |
| 2018 | Outstanding Graduate, Beijing Municipal Commission of Education |
| 2015, 2016, 2017 | National Undergraduate Scholarship, Ministry of Education of China |