Research Brief | SIAS Collection in Computer Science Conference Proceedings - Multimedia, Software Engineering, Robotics

Source:上海高等研究院英文网

In 2023, Shanghai Institute for Advanced Study, Zhejiang University has participated in multiple international conferences in multi-media research, software engineering and robotics. Below is a list of selected work:

Mengze Li, Haoyu Zhang, Juncheng Li, Zhou Zhao, Wenqiao Zhang, Shengyu Zhang, Shiliang Pu, Yueting Zhuang, Fei Wu:

Unsupervised Domain Adaptation for Video Object Grounding with Cascaded Debiasing Learning.

ACM Multimedia 2023: 3807-3816

https://dlnext.acm.org/doi/abs/10.1145/3581783.3612314

 

Haonan Shi, Wenwen Pan, Zhou Zhao, Mingmin Zhang, Fei Wu:

Unsupervised Domain Adaptation for Referring Semantic Segmentation.

ACM Multimedia 2023: 5807-5818

https://dl.acm.org/doi/10.1145/3581783.3611879

 

Yuqing Zhang, Zhou Fang, Xinyu Yang, Shengyu Zhang, Baoyi He, Huaiyong Dou, Junchi Yan, Yongquan Zhang, Fei Wu:

Reconnecting the Broken Civilization: Patchwork Integration of Fragments from Ancient Manuscripts.

ACM Multimedia 2023: 1157-1166

https://dl.acm.org/doi/pdf/10.1145/3581783.3613804

 

Mengze Li, Haoyu Zhang, Juncheng Li, Zhou Zhao, Wenqiao Zhang, Shengyu Zhang, Shiliang Pu, Yueting Zhuang, Fei Wu:

Unsupervised Domain Adaptation for Video Object Grounding with Cascaded Debiasing Learning.

ACM Multimedia 2023: 3807-3816

https://dl.acm.org/doi/10.1145/3581783.3612314

 

Haonan Shi, Wenwen Pan, Zhou Zhao, Mingmin Zhang, Fei Wu:

Unsupervised Domain Adaptation for Referring Semantic Segmentation.

ACM Multimedia 2023: 5807-5818

https://dl.acm.org/doi/10.1145/3581783.3611879

 

Didi Zhu, Yinchuan Li, Yunfeng Shao, Jianye Hao, Fei Wu, Kun Kuang, Jun Xiao, Chao Wu:

Generalized Universal Domain Adaptation with Generative Flow Networks.

ACM Multimedia 2023: 8304-8315

https://dl.acm.org/doi/10.1145/3581783.3611879

 

Tao Jin, Xize Cheng, Linjun Li, Wang Lin, Ye Wang, Zhou Zhao:

Rethinking Missing Modality Learning from a Decoding Perspective.

ACM Multimedia 2023: 4431-4439

https://dl.acm.org/doi/abs/10.1145/3581783.3612291

 

Zhiqing Hong, Chenye Cui, Rongjie Huang, Lichao Zhang, Jinglin Liu, Jinzheng He, Zhou Zhao:

UniSinger: Unified End-to-End Singing Voice Synthesis With Cross-Modality Information Matching.

ACM Multimedia 2023: 7569-7579

https://dl.acm.org/doi/10.1145/3581783.3612150

 

Jiajie Su, Chaochao Chen, Zibin Lin, Xi Li, Weiming Liu, Xiaolin Zheng:

Personalized Behavior-Aware Transformer for Multi-Behavior Sequential Recommendation.

ACM Multimedia 2023: 6321-6331

https://dl.acm.org/doi/10.1145/3581783.3611723

 

Cheng Jin, Liang He, Mingli Song, Rui Wang:

McGE '23: 1st International Workshop on Multimedia Content Generation and Evaluation: New Methods and Practice.

ACM Multimedia 2023: 9721-9722

https://dl.acm.org/doi/proceedings/10.1145/3607541


Xiaoxue Ren, Xinyuan Ye, Dehai Zhao, Zhenchang Xing, Xiaohu Yang:

From Misuse to Mastery: Enhancing Code Generation with Knowledge-Driven AI Chaining.

ASE 2023: 976-987

https://ieeexplore.ieee.org/document/10298349

 

Xing Hu, Zhuang Liu, Xin Xia, Zhongxin Liu, Tongtong Xu, Xiaohu Yang:

Identify and Update Test Cases When Production Code Changes: A Transformer-Based Approach.

ASE 2023: 1111-1122

https://ieeexplore.ieee.org/document/10298577

 

Chao Ni, Xinrong Guo, Yan Zhu, Xiaodan Xu, Xiaohu Yang:

Function-Level Vulnerability Detection Through Fusing Multi-Modal Knowledge.

ASE 2023: 1911-1918

https://ieeexplore.ieee.org/document/10298584

 

Chao Ni, Kaiwen Yang, Yan Zhu, Xiang Chen, Xiaohu Yang:

Unifying Defect Prediction, Categorization, and Repair by Multi-Task Deep Learning.

ASE 2023: 1980-1992

https://ieeexplore.ieee.org/document/10298436


Haoyuan Fu, Wenqiang Xu, Ruolin Ye, Han Xue, Zhenjun Yu, Tutian Tang, Yutong Li, Wenxin Du, Jieyi Zhang, Cewu Lu:

Demonstrating RFUniverse: A Multiphysics Simulation Platform for Embodied AI.

Robotics: Science and Systems 2023

https://www.roboticsproceedings.org/rss19/p087.pdf 

 

Jun Lv, Yunhai Feng, Cheng Zhang, Shuang Zhao, Lin Shao, Cewu Lu:

SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering.

Robotics: Science and Systems 2023

https://roboticsproceedings.org/rss19/p040.html