I am working for Ph.D. degree in Nanjing University with Professor Qing Gu (顾庆) and Assistant Professor Zhiwei Jiang (蒋智威). Currently, I am also a research intern at Tencent AI Lab, mentored by Kuan Tian (田宽) and Jun Zhang (张军).
I possess a wide-ranging interest in computer vision and deep learning. Currently, my focus is on controllable and consistent generation in AIGC, such as audio-driven video generation, text-to-image generation, and so on. My prior research experience spans various fields, including essay scoring, ordinal classification, and so on.
My B.Eng. degree was received from Nanjing Institute of Technology in June 2019. In the same year, I was admitted to study for M.Eng. degree in Nanjing University.
Experience
- 2023.05 – Present, Research Intern,
Tencent AI Lab, Technology & Engineering Group (TEG), Tencent, Shenzhen, China. - 2021.09 – Present, Ph.D. Student,
Department of Computer Science and Technology, Nanjing University, Nanjing, China. - 2019.09 – 2021.08, M.Eng.,
Department of Computer Science and Technology, Nanjing University, Nanjing, China. - 2015.09 – 2019.06, B.Eng.,
School of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, China.
Honors and Awards
- Outstanding Graduate Student, Nanjing University, 2023.
- Huawei Scholarship, Nanjing University, 2023.
- Yingcai Scholarship, Nanjing University, 2021.
Selected Publications
All Publications
2024
- Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models, F. Shen*, H. Ye*, J. Zhang†, C. Wang, X. Han, W. Yang, International Conference on Learning Representations (ICLR).
2023
- Learning Event-Specific Localization Preferences for Audio-Visual Event Localization, S. Ge, Z. Jiang†, Y. Yin, C. Wang, Z. Cheng, Q. Gu, ACM International Conference on Multimedia (MM).
- Aggregating Multiple Heuristic Signals as Supervision for Unsupervised Automated Essay Scoring, C. Wang, Z. Jiang†, Y. Yin, Z. Cheng, S. Ge, Q. Gu, Annual Meeting of the Association for Computational Linguistics (ACL).
- Unsupervised Readability Assessment via Learning from Weak Readability Signals, Y. Liu, Z. Jiang†, Y. Yin, C. Wang, S. Chen, Z. Chen, Q. Gu, International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR).
- Learning Robust Multi-Modal Representation for Multi-Label Emotion Recognition via Adversarial Masking and Perturbation, S. Ge, Z. Jiang†, Z. Cheng, C. Wang, Y. Yin, Q. Gu, The ACM Web Conference (WWW).
- Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning, C. Wang, Z. Jiang†, Y. Yin, Z. Cheng, S. Ge, Q. Gu, AAAI Conference on Artificial Intelligence (AAAI).
2022
- A Consistent Dual-MRC Framework for Emotion-Cause Pair Extraction, Z. Cheng, Z. Jiang†, Y. Yin, C. Wang, S. Ge, Q. Gu, ACM Transactions on Information Systems (TOIS).
- Learning to Classify Open Intent via Soft Labeling and Manifold Mixup, Z. Cheng, Z. Jiang†, Y. Yin, C. Wang, Q. Gu, IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP).
- Siamese Adversarial Network for Image Classification of Heavy Mineral Grains, H. Hao, Z. Jiang†, S. Ge, C. Wang, Q. Gu, Computers & Geosciences.
2021
- SiamFuseNet: A Pseudo-Siamese Network for Detritus Detection from Polarized Microscopic Images of River Sands, C. Wang, S. Ge, Z. Jiang, H. Hao, Q. Gu†, Computers & Geosciences.
- Dual-Input Attention Network for Automatic Identification of Detritus from River Sands, S. Ge, C. Wang, Z. Jiang, H. Hao, Q. Gu†, Computers & Geosciences.
* denotes equal contribution. † denotes the corresponding author.
Academic Services
- Member: ACL, AAAI.
- Conference Reviewer: ICIC (24), MM (24, 23), EMNLP (23).