Dandan Tu

According to our database, Dandan Tu authored at least 31 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Crafting Personalized Agents through Retrieval-Augmented Generation on Editable Memory Graphs.

Zheng Wang, Zhongyang Li, Zeren Jiang, Dandan Tu, Wei Shi

CoRR, 2024

ToolACE: Winning the Points of LLM Function Calling.

Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen

CoRR, 2024

Disfluency Detection for Real-World Scenarios.

Jianbang Ding, Suiyun Zhang, Dandan Tu

Proceedings of the International Joint Conference on Neural Networks, 2024

Concise and Precise Context Compression for Tool-Using Language Models.

Yang Xu, Yunlong Feng, Honglin Mu, Yutai Hou, Yitong Li, Xinghao Wang, Wanjun Zhong, Zhongyang Li, Dandan Tu, Qingfu Zhu, Min Zhang, Wanxiang Che

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Learning Fine-Grained Grounded Citations for Attributed Large Language Models.

Lei Huang, Xiaocheng Feng, Weitao Ma, Yuxuan Gu, Weihong Zhong, Xiachong Feng, Weijiang Yu, Weihua Peng, Duyu Tang, Dandan Tu, Bing Qin

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Unsupervised Cross-Modality Adaptation via Dual Structural-Oriented Guidance for 3D Medical Image Segmentation.

Junlin Xian, Xiang Li, Dandan Tu, Senhua Zhu, Changzheng Zhang, Xiaowu Liu, Xin Li, Xin Yang

IEEE Trans. Medical Imaging, June, 2023

DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF.

Chaowei Liu, Jichun Li, Yihua Teng, Chaoqun Wang, Nuo Xu, Jihao Wu, Dandan Tu

CoRR, 2023

Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning.

Dapeng Li, Feiyang Pan, Jia He, Zhiwei Xu, Dandan Tu, Guoliang Fan

CoRR, 2023

Stable Attribute Group Editing for Reliable Few-shot Image Generation.

Guanqi Ding, Xinzhe Han, Shuhui Wang, Xin Jin, Dandan Tu, Qingming Huang

CoRR, 2023

Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning.

Shuo Yu, Hongyan Xue, Xiang Ao, Feiyang Pan, Jia He, Dandan Tu, Qing He

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Gradient-Adaptive Pareto Optimization for Constrained Reinforcement Learning.

Zixian Zhou, Mengda Huang, Feiyang Pan, Jia He, Xiang Ao, Dandan Tu, Qing He

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2022

Intrinsic Bias Identification on Medical Image Datasets.

Shijie Zhang, Lanjun Wang, Lian Ding, An-An Liu, Senhua Zhu, Dandan Tu

CoRR, 2022

Attribute Group Editing for Reliable Few-shot Image Generation.

Guanqi Ding, Xinzhe Han, Shuhui Wang, Shuzhe Wu, Xin Jin, Dandan Tu, Qingming Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency.

Zhenhuan Liu, Liang Li, Huajie Jiang, Xin Jin, Dandan Tu, Shuhui Wang, Zheng-Jun Zha

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2021

Deep learning for predicting COVID-19 malignant progression.

Cong Fang, Song Bai, Qianlan Chen, Yu Zhou, Liming Xia, Lixin Qin, Shi Gong, Xudong Xie, Chunhua Zhou, Dandan Tu, Changzheng Zhang, Xiaowu Liu, Weiwei Chen, Xiang Bai, Philip H. S. Torr

Medical Image Anal., 2021

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia

CoRR, 2021

DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19.

Chengtao Peng, Yunfei Long, Senhua Zhu, Dandan Tu, Bin Li

CoRR, 2021

DuCN: Dual-Children Network for Medical Diagnosis and Similar Case Recommendation Towards COVID-19.

Yunfei Long, Senhua Zhu, Dandan Tu

Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021

2020

Trust the Model When It Is Confident: Masked Model-based Actor-Critic.

Feiyang Pan, Jia He, Dandan Tu, Qing He

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Pay More Attention to Discontinuity for Medical Image Segmentation.

Jiajia Chu, Yajie Chen, Wei Zhou, Heshui Shi, Yukun Cao, Dandan Tu, Ri-Chu Jin, Yongchao Xu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Learning Directional Feature Maps for Cardiac MRI Segmentation.

Feng Cheng, Cheng Chen, Yukang Wang, Heshui Shi, Yukun Cao, Dandan Tu, Changzheng Zhang, Yongchao Xu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

MSAFusionNet: Multiple Subspace Attention Based Deep Multi-modal Fusion Network.

Sen Zhang, Changzheng Zhang, Lanjun Wang, Cixing Li, Dandan Tu, Rui Luo, Guojun Qi, Jiebo Luo

Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

DCCL: A Benchmark for Cervical Cytology Analysis.

Changzheng Zhang, Dong Liu, Lanjun Wang, Yaoxin Li, Xiaoshi Chen, Rui Luo, Shuanlong Che, Hehua Liang, Yinghua Li, Si Liu, Dandan Tu, Guojun Qi, Pifu Luo, Jiebo Luo

Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

2018

Face Detection Using Improved Faster RCNN.

Changzheng Zhang, Xiang Xu, Dandan Tu

CoRR, 2018

A unified scheme of text localization and structured data extraction for joint OCR and data mining.

Yibin Ye, Shenggao Zhu, Jing Wang, Qi Du, Yezhang Yang, Dandan Tu, Lanjun Wang, Jiebo Luo

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

A Survey on Deep Learning Benchmarks: Do We Still Need New Ones?

Qin Zhang, Li Zha, Jian Lin, Dandan Tu, Mingzhe Li, Fan Liang, Ren Wu, Xiaoyi Lu

Proceedings of the Benchmarking, Measuring, and Optimizing, 2018

2011

Three New Concepts of Future Computer Science.

Zhiwei Xu, Dandan Tu

J. Comput. Sci. Technol., 2011

2010

Rank Internet Service Quality Using Multiple Features: A Machine Learning Approach.

Dandan Tu, Chengchun Shu, Jingwei Shi, Tao Zhu, Shuang Wang, Haiyan Yu

Proceedings of the Sixth International Conference on Semantics Knowledge and Grid, 2010

2009

XConveryer: Guarantee Hadoop Throughput via Lightweight OS-Level Virtualization.

An Qin, Dandan Tu, Chengchun Shu, Chang Gao

Proceedings of the Eighth International Conference on Grid and Cooperative Computing, 2009