Qiang Sheng

Qiang Sheng 盛强

I am an Associate Professor/Researcher at the Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences. I am also a supervisor at School of Computer Science and Technology, University of Chinese Academy of Sciences (UCAS), where I got my Ph.D. degree under the supervision of Professor Juan Cao. My research interests include:

  • Application: Fake News/Misinformation Detection, Fact-Checking, Machine-Generated Content Detection
  • Direction: Natural Language Understanding and Social Media Mining
  • Vision: Make the World More Credible

Contact: shengqiang18z AT ict dot ac dot cn

GitHub    /    Google Scholar    /    ResearchGate    /    ORCID    /    DBLP    /    Zhihu Column    /    ACL Anthology    /    IR Anthology

✍   Hightlights

- Github Repo (Maintaining): Awesome-Generated-Text, LLM-for-misinformation-research

- I will have one position enrolled in Sep. 2026, and also recruit highly motivated research interns (1-2 positions, onsite preferred). Anyone who is interested in combating misinformation in the era of large language models may send me their resume by email.

News

  • 09/2025 One co-authored paper got accepted by AAAI 2026.
  • 09/2025 One co-authored paper got accepted by NeurIPS 2025.
  • 08/2025 Two co-authored papers got accepted by EMNLP 2025 Main/Findings.
  • 08/2025 Two co-authored papers on fake news detection got accepted by CIKM 2025.
  • 07/2025 Received the Best PC Member Award (among 20 awardees) at SIGIR 2025.
  • 06/2025 Will present our recent work on fake news detection at YSSNLP 2025.
  • 02/2025 Will serve as an Area Chair and co-offer a tutorial named Combating Online Misinformation Videos: Characterization, Detection, and Prevention at MM 2025. See you in Dublin!
  • 10/2024 Recognized as an Outstanding Area Chair at MM 2024.
  • 10/2024 Will introduce our latest works on LLM-driven misinformation detection at SMP 2024.
Full List

Publications

Preprints

PhantomHunter: Detecting Unseen Privately-Tuned LLM-Generated Text via Family-Aware Learning
Yuhui Shi, Yehan Yang, Qiang Sheng, Hao Mi, Beizhe Hu, Chaoxi Xu, and Juan Cao
Preprint / Media Coverage: Unite.AI

2026

IEEE TVCG Interactive Visual Assessment for Text-to-Image Generation Models
Xiaoyue Mi, Fan Tang, Juan Cao, Qiang Sheng, Ziyao Huang, Peng Li, Yang Liu, Tong-Yee Lee
IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG)
Preprint / BibTeX
EACL'26 Tailoring Rumor Debunking to You: Diversifying Chinese Rumor-Debunking Passages with an LLM-Driven Simulated Feedback-Enhanced Framework
Xinle Pang, Danding Wang, Qiang Sheng, Yifan Sun, Beizhe Hu, and Juan Cao
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics
Paper (TBA) / BibTeX
TL;DR: We build an LLM-driven framework that generates rumor-debunking passages for various groups of people.
AAAI'26 Reasoning About the Unsaid: Misinformation Detection with Omission-Aware Graph Inference
Zhengjia Wang, Danding Wang, Qiang Sheng, Jiaying Wu, and Juan Cao
Proceedings of the 40th AAAI Conference on Artificial Intelligence (Acceptance Rate: 4167/23680=17.60%)
Preprint / BibTeX
TL;DR: We consider the omitted information to better reason the creator's intent for misinformation detection.

2025

NeurIPS'25 From Judgment to Interference: Early Stopping LLM Harmful Outputs via Streaming Content Monitoring
Yang Li, Qiang Sheng, Yehan Yang, Xueyao Zhang, and Juan Cao
Proceedings of the 39th Annual Conference on Neural Information Processing Systems (Acceptance Rate: 5290/21575=24.52%)
Preprint / Paper (TBA) / Project Page / Github Repo / Chinese Blog / Chinese Video / BibTeX
TL;DR: We build a content moderator that can early stop LLMs' harmful outputs with low latency.
EMNLP'25 The Staircase of Ethics: Probing LLM Value Priorities through Multi-Step Induction to Complex Moral Dilemmas
Ya Wu, Qiang Sheng, Danding Wang, Guang Yang, Yifan Sun, Zhengjia Wang, Yuyan Bu, and Juan Cao
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (Acceptance Rate: 1811/8174=22.16%)
Preprint / Paper / Project Page / Chinese Blog / BibTeX
TL;DR: We build the MMD benchmark to probe the LLMs' value preferences in complex moral dilemmas.
EMNLP'25 Findings Forewarned is Forearmed: Pre-Synthesizing Jailbreak-like Instructions to Enhance LLM Safety Guardrail to Potential Attacks
Sheng Liu, Qiang Sheng, Danding Wang, Yang Li, Guang Yang, and Juan Cao
Preprint / Paper / Chinese Blog
Findings of the Association for Computational Linguistics: EMNLP 2025 (Acceptance Rate: 1417/8174=17.34%) / BibTeX
TL;DR: We enhance LLM resistance to jailbreaking by synthesizing instructions that may fall into the potentially risky space.
CIKM'25 Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection
Zhengjia Wang, Qiang Sheng, Danding Wang, Beizhe Hu, and Juan Cao
Proceedings of the 34th ACM International Conference on Information and Knowledge Management (Acceptance Rate: 443/1627=27.2%)
Preprint / Paper / Chinese Blog / BibTeX
TL;DR: We propose to inject intent information with graph-based joint learning into fake news detection.
CIKM'25 Enhancing Fake News Video Detection via LLM-Driven Creative Process Simulation
Yuyan Bu, Qiang Sheng, Juan Cao, Shaofei Wang, Peng Qi, Yuhui Shi, and Beizhe Hu
Proceedings of the 34th ACM International Conference on Information and Knowledge Management (Acceptance Rate: 185/604=30.6%)
Preprint / Paper / Media Coverage: 52CV / BibTeX
TL;DR: We propose AgentAug, which simulates the creative process of fake news videos using LLMs to mitigate the data scarcity issue.
IP&M Exploring News Intent and Its Application: A Theory-Driven Approach
Zhengjia Wang, Danding Wang, Qiang Sheng, Juan Cao, Siyuan Ma, and Haonan Cheng
Preprint / Paper / Chinese Blog
Information Processing and Management, 2025 / BibTeX
TL;DR: We, for the first time, conceptualize and computerize news intent modeling and showcase its application on fake news detection, popularity prediction, and propaganda detection.
ACL'25 Findings Enhancing the Comprehensibility of Text Explanations via Unsupervised Concept Discovery
Yifan Sun, Danding Wang, Qiang Sheng, Juan Cao, and Jintao Li
Preprint / Paper / Chinese Blog
Findings of the Association for Computational Linguistics: ACL 2025 / BibTeX
TL;DR: We exploit LLMs to automatically discover key concepts for text classification to enhance the comprehensibility of text explanations.
SIGIR'25 LLM-Generated Fake News Induces Truth Decay in News Ecosystem: A Case Study on Neural News Recommendation
Beizhe Hu, Qiang Sheng, Juan Cao, Yang Li, and Danding Wang
Proceedings of The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (Acceptance Rate: 239/1071=22.3%)
Preprint / Paper / Project Page / BibTeX
TL;DR: We reveal the truth-decay phenomenon where real news gradually loses its top-ranked advantage against fake news when LLM-generated news penetrates.
CAS Bulletin Challenges on Public Security System in AI Era
Juan Cao, Qiang Sheng, Guojie Li
Bulletin of Chinese Academy of Sciences
Paper / Media Coverage: 中国教育报, 新华文摘 / BibTeX
TL;DR: We discussed new challenges and countermeasures in public security brought by AIGC techniques.
FCS Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting
Qiong Nan, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Guang Yang, and Jintao Li
Frontiers of Computer Science
Preprint / Paper / BibTeX
TL;DR: We explored how to let a comment-based model effectively help a content-only one in fake news early detection.

2024

CIKM'24 Let Silence Speak: Enhancing Fake News Detection with Generated Comments from Large Language Models
Qiong Nan, Qiang Sheng, Juan Cao, Beizhe Hu, Danding Wang, and Jintao Li
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (Acceptance Rate: 347/1496=23.2%)
Preprint / Paper / GitHub Repo / Chinese Blog / BibTeX
TL;DR: We prompt LLMs to role-play social media users to obtain generated comments for enhancing fake news detection.
MM'24 FakingRecipe: Detecting Fake News on Short Video Platforms from the Perspective of Creative Process
Yuyan Bu, Qiang Sheng, Juan Cao, Peng Qi, Danding Wang, and Jintao Li
Proceedings of the 32nd ACM International Conference on Multimedia (Acceptance Rate: 1149/4385=26.2%)
Preprint / Paper / GitHub Repo / Chinese Blog / CSIG MM论文导读 / BibTeX
TL;DR: We detect fake news on short video platforms by modeling videos from the faking process perspective and constructed a FakeSV's sister dataset in English, namely FakeTT.
IJCAI'24 Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Sampling
Yuhui Shi, Qiang Sheng, Juan Cao, Hao Mi, Beizhe Hu, and Danding Wang
Proceedings of the 33rd International Joint Conference on Artificial Intelligence (Acceptance Rate: 791/5651=14.0%)
Preprint / Paper / GitHub Repo / Slides / Chinese Blog / BibTeX
TL;DR: To detect and attribute text generated by black-box LMs, we estimate their generation probabilities of representative words guided by a white-box proxy LM to obtain a strong feature.
IJCAI'24 Vision-fused Attack: Advancing Aggressive and Stealthy Adversarial Text against Neural Machine Translation
Yanni Xue, Haojie Hao, Jiakai Wang, Qiang Sheng, Renshuai Tao, Yu Liang, Pu Feng, and Xianglong Liu
Proceedings of the 33rd International Joint Conference on Artificial Intelligence (Acceptance Rate: 791/5651=14.0%)
Paper / GitHub Repo / Chinese Blog / BibTeX
TL;DR: We propose a vision-fused attack framework to acquire powerful adversarial text (i.e., more aggressive and stealthy) in neural machine translation.
AAAI'24 Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection
Beizhe Hu, Qiang Sheng, Juan Cao, Yuhui Shi, Yang Li, Danding Wang, and Peng Qi
Proceedings of the 38th AAAI Conference on Artificial Intelligence
Preprint / Paper / GitHub Repo / English Video & Slides / BibTeX
TL;DR: Large LMs generally underperform fine-tuned Small LMs for fake news detection, but they can be good advisors by providing rationales.

2023

CCCF The Safety in the AIGC era: Techniques Make the World More Credible (AIGC时代的安全：用技术让世界更可信)
Juan Cao, and Qiang Sheng
Communications of the China Computer Federation, October 2023
Paper / WeChat Release / BibTeX
TL;DR: Our perspective paper on the safety issues brought by AI-generated content.
MM'23 Combating Online Misinformation Videos: Characterization, Detection, and Future Directions
Yuyan Bu, Qiang Sheng, Juan Cao, Peng Qi, Danding Wang, and Jintao Li
Proceedings of the 31st ACM International Conference on Multimedia (Acceptance Rate: 902/3669=24.6%)
Preprint / Paper / GitHub Repo / Chinese Blog / BibTeX
TL;DR: We conduct the very first survey focusing on online misinformation video detection, to the best of our knowledge.
ACL'23 Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection
Beizhe Hu, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Zhengjia Wang, and Zhiwei Jin
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics
Preprint / Paper / Code / Poster / Slides / English Video / Explanatory AI arXiv Weekly Roundup
TL;DR: We propose to address the temporal shift issue in real-world fake news detection systems via forecasting topic-level trends and accordingly adjusting the detector update strategy.

2022

COLING'22 Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer
Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, and Jintao Li
Proceedings of the 29th International Conference on Computational Linguistics (Acceptance Rate: 632/2253=28.1%)
Preprint / Paper / Code / English Video / Chinese Blog 1/ 2
TL;DR: We propose a domain- and instance-level transfer framework for detecting fake news of target domains.
IEEE TKDE Memory-Guided Multi-View Multi-Domain Fake News Detection
Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, and Fuzhen Zhuang
IEEE Transactions on Knowledge and Data Engineering, 2022
Preprint / Paper / 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.
IP&MCharacterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo
Qiang Sheng, Juan Cao, H. Russell Bernard, Kai Shu, Jintao Li, and Huan Liu
Information Processing and Management, 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.
SIGIR'22 Generalizing to the Future: Mitigating Entity Bias in Fake News Detection
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 / Code / 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.
ACL'22 Zoom Out and Observe: News Environment Perception for Fake News Detection
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 (Acceptance Rate: 701/3378=20.75%)
Preprint / Paper / Poster / Code / Dataset / Chinese Video / Chinese Blog / English Video / English Blog
TL;DR: For the first time, we propose to perceive signals from the news environment for fake news detection.
AAAI'22 DRAG: Dynamic Region-Aware GCN for Privacy-Leaking Image Detection
Guang Yang, Juan Cao, Qiang Sheng, Peng Qi, Xirong Li, and Jintao Li
Proceedings of the 36th AAAI Conference on Artificial Intelligence (Acceptance Rate: 1349/9020=15.0%)
Preprint / Paper / English Video
TL;DR: We propose a GCN-based method to find out crucial privacy-indicative regions for privacy-leaking image detection dynamically.

2021

MM'21 Improving Fake News Detection by Using an Entity-enhanced Framework to Fuse Diverse Multimodal Clues
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
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.
CIKM'21 Integrating Pattern- and Fact-based Fake News Detection via Model Preference Learning
Qiang Sheng*, Xueyao Zhang*, Juan Cao, and Lei Zhong (*:Equal Contribution)
Proceedings of the 30th ACM International Conference on Information and Knowledge Management (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.
ACL'21 Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Claims
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 (Acceptance Rate:571/2327=24.5%)
Preprint / Paper / Poster / Code / Chinese Dataset / English Video / Chinese Blog 1/ 2/ 3
TL;DR: We detect previously fact-checked claims by matching them against the key sentences in fact-checking articles.
J-CRAD Semantics-Enhanced Multi-modal Fake News Detection (语义增强的多模态虚假新闻检测)
Peng Qi, Juan Cao, and Qiang Sheng
Journal of Computer Research 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.
WWW'21 Mining Dual Emotion for Fake News Detection
Xueyao Zhang, Juan Cao, Xirong Li, Qiang Sheng, Lei Zhong, and Kai Shu
Proceedings of the 30th Web Conference (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.

2020

ACL'20 Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection
Lei Zhong, Juan Cao, Qiang Sheng, Junbo Guo, and Ziang Wang
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (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.
CCCF Fake News and Disinformation Detection on the Internet: Recent Advances and Future Prospects (互联网虚假信息检测进展与展望)
Juan Cao, Qiang Sheng, and Peng Qi
Communications of the China Computer Federation, March 2020
Webpage Version / WeChat Release
TL;DR: We review the recent advances of detecting fake news and disinformation and propose potential directions.
Springer Book Chapter Exploring the Role of Visual Content in Fake News Detection
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.

Tutorials

MM'25 Combating Online Misinformation Videos: Characterization, Detection, and Prevention
Qiang Sheng, Peng Qi, Tianyun Yang, Yuyan Bu, Wynne Hsu, Mong Li Lee, and Juan Cao
The 33rd ACM International Conference on Multimedia (MM 2025)
Webpage / ACM DL
SIGIR'24 Preventing and Detecting Misinformation Generated by Large Language Models
Aiwei Liu, Qiang Sheng, and Xuming Hu
The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)
Webpage / ACM DL

Talks

  • 2025/11/15 Advances and Changes of Misinformation Detection in the LLM era
    大模型时代虚假信息检测的发展与变化
    @ People's Public Security University of China
  • 2025/9/11 Advances and Changes of Misinformation Detection in the LLM era
    大模型时代虚假信息检测的发展与变化
    @ Institute of Information Engineering, Chinese Academy of Sciences
  • 2025/6/28 Content Safety in the LLM era: From Detection to Interference
    大模型时代的内容安全：从识别到干预
    @ The Youth Forum on AI Language Capabilities and Safety Governance, Beijing Foreign Studies University (Event)
  • 2025/6/14 Advances and Changes of Misinformation Detection in the LLM era
    大模型时代虚假信息检测的发展与变化
    @ YSSNLP 2025 (Event)
  • 2025/1/16 LLMs and Misinformation Detection
    大模型与虚假信息检测
    @ AI TIME (Event)
  • 2024/11/8 Misinformation Detection in the Era of LLMs: Recent Advances and Discussions
    大模型时代的虚假信息检测：进展与探讨
    @ Institute of Information Engineering, Chinese Academy of Sciences (Event)
  • 2024/10/12 LLM-Driven Internet Misinformation Rehearsal and Detection Enhancement
    大模型驱动的互联网虚假信息预演及检测增强
    @ SMP 2024 (Event)
  • 2024/6/1 AIGC: Techniques, Challenges, and Countermeasures
    AIGC: 技术、挑战和应对
    @ Beijing Film Academy (Event)
  • 2023/6/28 Improving Research Zooming Capability: Three Views of Application Research
    提升科研“变焦”能力：应用问题研究的三个视角
    @ Advanced Computing Technology Seminar, ICT, CAS
  • 2023/6/8 Generalization and Multi-Modality Issues in Real-World Fake News Detection and Beyond
    @ Illinois Institute of Technology
  • 2023/3/3 The Birth of Papers on Top-Tier Journals and Conferences: Works Done Behind
    顶会顶刊论文的诞生：你看不到的那些工作
    @ Student Career Development Association, ICT, CAS
  • 2023/3/1 ChatGPT: Techniques, Impacts, and Countermeasures
    ChatGPT: 技术、影响和应对
    @ Ruijian AI
  • 2023/3/1 ChatGPT: Techniques, Impacts, and Countermeasures
    ChatGPT: 技术、影响和应对
    @ Beijing Film Academy (Event)
  • 2022/12/30 Towards Real-World Fake News Detection
    @ Tsinghua University
  • 2022/12/17 Three Views of Application Research: Cases in Fake News Detection
    应用问题研究的三个视角：以虚假新闻检测为例
    @ CSSNLP 2022 (Event / Video)
  • 2022/10/4 Zoom Out and Observe: News Environment Perception for Fake News Detection
    新闻环境感知下的虚假新闻检测
    @ MLNLP Paper Reading (Event / Video)
  • 2022/9/2 Online Fake News Detection: Method, System, and Thinking
    @ Baidu Search
  • 2022/8/31 Online Fake News Detection: Method, System, and Thinking
    @ ByteDance AI Lab
  • 2022/5/14 Zoom Out and Observe: News Environment Perception for Fake News Detection
    新闻环境感知下的虚假新闻检测
    @ AIS 2022 (NLU Session) (Event / Video)
  • 2022/4/24 Zoom Out and Observe: News Environment Perception for Fake News Detection
    新闻环境感知下的虚假新闻检测
    @ BUAFAI 2022 (NLP & Speech Forum) (Event / Video)
  • 2022/4/20 Zoom Out and Observe: News Environment Perception for Fake News Detection
    新闻环境感知下的虚假新闻检测
    @ AI TIME Live (Event / Video / WeChat Article)

Teaching Experience

  • 2020/2021 Spring Teaching Assistant, 081203M05008H: Multimedia Technology, UCAS

Academic Services

Area Chair/SPC Member

MM 2024 (Outstanding Area Chair), 2025
ACL Rolling Review (Oct. 2025~)
ICMR 2026
IJCAI 2026

Conf. Reviewer/PC Member

AAAI 2022, 2023, 2024, 2025, 2026
ACL 2022, 2023, 2024, 2025, 2026
ACL Rolling Review (Nov. 2021~July 2025), Great Reviews Marked in: Oct. 2023, Apr. 2024, Feb. 2025, May 2025)
CIKM 2023, 2024, 2025
CSCW 2021 (Recognized for Excellent Reviewing)
CVPR 2026
EACL 2023, 2024, 2026
ECML-PKDD 2023, 2024, 2025, 2026
EMNLP 2021, 2022, 2023, 2024, 2025
ICME 2025
IJCAI 2023, 2024, 2025
KDD 2023, 2024
MM 2023
NAACL 2022 (Outstanding Reviewer), 2024, 2025
NeurIPS 2025 (Top Reviewer)
NLPCC 2024, 2025
SDM 2024
SIGIR 2023, 2024, 2025 (Best PC Member Award), 2026
SIGIR-AP 2023
TheWebConf (WWW) 2023, 2024, 2025, 2026
WSDM 2026

Journal Reviewer

ACM Transactions on Information Systems (TOIS)
Computational Intelligence
IEEE Transactions on Audio, Speech and Language Processing (TASLP)
IEEE Transactions on Computational Social Systems (TCSS)
IEEE Transactions on Information Forensics and Security (TIFS)
IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Multimedia (TMM)
Information Processing and Management (IP&M)
Journal of Computer Research and Development (计算机研究与发展)
Multimedia Systems
Social Network Analysis and Mining

Student Volunteer

IEEE ICDM 2019

Education

Honors and Awards

  • 2024 Star of Excellence, ICT, CAS
  • 2023 Excellent Prize of the President Scholarship, CAS
  • 2023 Special Prize of the President Scholarship, ICT, CAS
  • 2022 Pacemaker to Merit Student of UCAS, UCAS
  • 2022 E Fund Scholarship, Guangdong E Fund Education Foundation & ICT, CAS
  • 2021, 2022 First-Class Academic Scholarship, University of Chinese Academy of Sciences
  • 2019, 2020 Merit Student, University of Chinese Academy of Sciences
  • 2018 Outstanding Graduate, Beijing Municipal Commission of Education
  • 2015, 2016, 2017, 2022 National Scholarship, Ministry of Education of China

Team Members and Alumni

  • Yuanlong Yu (2026-, Co-Supervised with Juan Cao)
  • Yehan Yang (2025-, Co-Supervised with Juan Cao)
  • Hao Mi (2024-, Co-Supervised with Juan Cao)
  • Yang Li (2023-, Co-Supervised with Juan Cao)
  • Sheng Liu (2023-, Co-Supervised with Juan Cao)
  • Ya Wu (2023-2026, Co-Supervised with Juan Cao and Danding Wang)
  • Yuyan Bu (2022-2025, Co-Supervised with Jintao Li, -> Beijing Academy of Artificial Intelligence)
  • Yuhui Shi (2022-2025, Co-Supervised with Juan Cao, -> The HQ of China Consturction Bank)
  • Zhengjia Wang (2021-, Co-Supervised with Juan Cao and Danding Wang)
  • Beizhe Hu (2021-, Co-Supervised with Juan Cao)
  • Qiong Nan (2019-2024, Co-Supervised with Jintao Li, -> CNCERT/CC)