SCAN: Structure Correcting Adversarial Network for Chest X-rays Organ Segmentation. - Wei Dai 003; Joseph Doyle; Xiaodan Liang; Hao Zhang 025; Nanqing Dong; Yuan Li 032; Eric P. Xing (CoRR, 2017)

Few-Shot Semantic Segmentation with Prototype Learning. - Nanqing Dong; Eric P. Xing (BMVC, 2018)

Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling. - Zeya Wang; Nanqing Dong; Wei Dai 003; Sean D. Rosario; Eric P. Xing (ICIAR, 2018)

SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays. - Wei Dai 003; Nanqing Dong; Zeya Wang; Xiaodan Liang; Hao Zhang 025; Eric P. Xing (DLMIA/ML-CDS@MICCAI, 2018)

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Zeya Wang; Wei Dai 003; Eric P. Xing (MICCAI (2), 2018)

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Zeya Wang; Wei Dai 003; Eric P. Xing (DLMIA/ML-CDS@MICCAI, 2018)

Domain Adaption in One-Shot Learning. - Nanqing Dong; Eric P. Xing (ECML/PKDD (1), 2018)

Toward Understanding the Impact of Staleness in Distributed Machine Learning. - Wei Dai 003; Yi Zhou 017; Nanqing Dong; Hao Zhang 025; Eric P. Xing (ICLR (Poster), 2019)

Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Images. - Zeya Wang; Nanqing Dong; Sean D. Rosario; Min Xu 009; Pengtao Xie; Eric P. Xing (ISBI, 2019)

Neural Architecture Search for Adversarial Medical Image Segmentation. - Nanqing Dong; Min Xu 009; Xiaodan Liang; Yiliang Jiang; Wei Dai 003; Eric P. Xing (MICCAI (6), 2019)

ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. - Michael Kampffmeyer; Nanqing Dong; Xiaodan Liang; Yujia Zhang 001; Eric P. Xing (IEEE Trans. Image Process., 2019)

Adversarial Domain Adaptation Being Aware of Class Relationships. - Zeya Wang; Baoyu Jing; Yang Ni; Nanqing Dong; Pengtao Xie; Eric P. Xing (ECAI, 2020)

Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Min Xu 009; Irina Voiculescu; Eric P. Xing (CoRR, 2020)

Quantum Unsupervised Domain Adaptation: Does Entanglement Help? - Nanqing Dong; Michael C. Kampffmeyer; Irina Voiculescu (BMVC, 2021)

Federated Contrastive Learning for Decentralized Unlabeled Medical Images. - Nanqing Dong; Irina Voiculescu (MICCAI (3), 2021)

Self-supervised Multi-task Representation Learning for Sequential Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu (ECML/PKDD (3), 2021)

Residual Contrastive Learning for Joint Demosaicking and Denoising. - Nanqing Dong; Matteo Maggioni; Yongxin Yang; Eduardo Pérez-Pellitero; Ales Leonardis; Steven McDonagh 001 (CoRR, 2021)

Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid. - Zhaoming Qin; Nanqing Dong; Eric P. Xing; Junwei Cao (CoRR, 2021)

Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity. - Nanqing Dong; Jiayi Wang 003; Irina Voiculescu (CVPR Workshops, 2022)

Computationally-Efficient Vision Transformer for Medical Image Semantic Segmentation Via Dual Pseudo-Label Supervision. - Ziyang Wang; Nanqing Dong; Irina Voiculescu (ICIP, 2022)

Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images. - Nanqing Dong; Matteo Maggioni; Yongxin Yang; Eduardo Pérez-Pellitero; Ales Leonardis; Steven McDonagh 001 (IJCAI, 2022)

Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu (MICCAI (8), 2022)

Towards robust partially supervised multi-structure medical image segmentation on small-scale data. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Min Xu 009; Irina Voiculescu; Eric P. Xing (Appl. Soft Comput., 2022)

FLock: Defending Malicious Behaviors in Federated Learning with Blockchain. - Nanqing Dong; Jiahao Sun; Zhipeng Wang 009; Shuoying Zhang; Shuhao Zheng (CoRR, 2022)

Region Proposal Network Pre-Training Helps Label-Efficient Object Detection. - Linus Ericsson; Nanqing Dong; Yongxin Yang; Ales Leonardis; Steven McDonagh 001 (CoRR, 2022)

Negational symmetry of quantum neural networks for binary pattern classification. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric P. Xing (Pattern Recognit., 2022)

Defending Against Malicious Behaviors in Federated Learning with Blockchain. - Nanqing Dong; Zhipeng Wang 009; Jiahao Sun; Michael Kampffmeyer; Yizhe Wen; Shuoying Zhang; William J. Knottenbelt; Eric P. Xing (CoRR, 2023)

zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning. - Zhipeng Wang 009; Nanqing Dong; Jiahao Sun; William J. Knottenbelt (CoRR, 2023)

Edge Computing with Artificial Intelligence: A Machine Learning Perspective. - Haochen Hua; Yutong Li; Tonghe Wang; Nanqing Dong; Wei Li 058; Junwei Cao (ACM Comput. Surv., 2023)

Federated Partially Supervised Learning With Limited Decentralized Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric P. Xing (IEEE Trans. Medical Imaging, 2023)

ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing. - Zhi Jin; Sheng Xu; Xiang Zhang 011; Tianze Ling; Nanqing Dong; Wanli Ouyang; Zhiqiang Gao; Cheng Chang; Siqi Sun (AAAI, 2024)

An Embarrassingly Simple Approach to Enhance Transformer Performance in Genomic Selection for Crop Breeding. - Renqi Chen; Wenwei Han; Haohao Zhang; Haoyang Su; Zhefan Wang; Xiaolei Liu; Hao Jiang; Wanli Ouyang; Nanqing Dong (IJCAI, 2024)

Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method. - Weizhen Liu; Ao Li; Ze Wu 007; Yue Li 039; Baobin Ge; Guangyu Lan; Shilin Chen; Minghe Li; Yunfei Liu; Xiaohui Yuan; Nanqing Dong (IJCAI, 2024)

Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection - Towards Precise Fish Morphological Assessment in Aquaculture Breeding. - Weizhen Liu; Jiayu Tan; Guangyu Lan; Ao Li; Dongye Li; Le Zhao; Xiaohui Yuan; Nanqing Dong (IJCAI, 2024)

Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA. - Lifeng Qiao; Peng Ye 006; Yuchen Ren 001; Weiqiang Bai; Chaoqi Liang; Xinzhu Ma; Nanqing Dong; Wanli Ouyang (NeurIPS, 2024)

Empowering and Assessing the Utility of Large Language Models in Crop Science. - Hang Zhang; Jiawei Sun; Renqi Chen; Wei Liu 123; Zhonghang Yuan; Xinzhe Zheng 001; Zhefan Wang; Zhiyuan Yang; Hang Yan 001; Han-Sen Zhong; Xiqing Wang; Wanli Ouyang; et al. (NeurIPS, 2024)

An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images. - Nanqing Dong; Michael Kampffmeyer; Haoyang Su; Eric P. Xing (Appl. Soft Comput., 2024)

Deep generative model for protein subcellular localization prediction. - Guo-Hua Yuan; Jinzhe Li; Zejun Yang; Yao-Qi Chen; Zhonghang Yuan; Tao Chen 003; Wanli Ouyang; Nanqing Dong; Li Yang (Briefings Bioinform., 2024)

Two Heads Are Better Than One: A Multi-Agent System Has the Potential to Improve Scientific Idea Generation. - Haoyang Su; Renqi Chen; Shixiang Tang; Xinzhe Zheng 001; Jingzhe Li; Zhenfei Yin; Wanli Ouyang; Nanqing Dong (CoRR, 2024)

COMET: Benchmark for Comprehensive Biological Multi-omics Evaluation Tasks and Language Models. - Yuchen Ren 001; Wenwei Han; Qianyuan Zhang; Yining Tang; Weiqiang Bai; Yuchen Cai; Lifeng Qiao; Hao Jiang; Dong Yuan; Tao Chen 003; Siqi Sun; Pan Tan; et al. (CoRR, 2024)

Biology Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models. - Haonan He; Yuchen Ren 001; Yining Tang; Ziyang Xu; Junxian Li 001; Minghao Yang; Di Zhang; Dong Yuan; Tao Chen 003; Shufei Zhang; Yuqiang Li; Nanqing Dong; et al. (CoRR, 2024)

Label-efficient object detection via region proposal network pre-training. - Nanqing Dong; Linus Ericsson; Yongxin Yang; Ales Leonardis; Steven McDonagh 001 (Neurocomputing, 2024)

Smoke veil prior regularized surgical field desmoking without paired in-vivo data. - Congcong Wang; Meng Zhao 001; Chengguang Zhou; Nanqing Dong; Zohaib Amjad Khan; Xintong Zhao; Faouzi Alaya Cheikh; Azeddine Beghdadi; Shengyong Chen (Comput. Biol. Medicine, 2024)

Defending Against Poisoning Attacks in Federated Learning With Blockchain. - Nanqing Dong; Zhipeng Wang 009; Jiahao Sun; Michael Kampffmeyer; William J. Knottenbelt; Eric P. Xing (IEEE Trans. Artif. Intell., 2024)

Towards Efficient and Intelligent Laser Weeding: Method and Dataset for Weed Stem Detection. - Dingning Liu; Jinzhe Li; Haoyang Su; Bei Cui; Zhihui Wang; Qingbo Yuan; Wanli Ouyang; Nanqing Dong (AAAI, 2025)

Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System. - Haoyang Su; Renqi Chen; Shixiang Tang; Zhenfei Yin; Xinzhe Zheng 001; Jinzhe Li; Biqing Qi; Qi Wu; Hui Li 037; Wanli Ouyang; Philip Torr 001; Bowen Zhou 002; et al. (ACL (1), 2025)

SeedBench: A Multi-task Benchmark for Evaluating Large Language Models in Seed Science. - Jie Ying; Zihong Chen; Zhefan Wang; Wanli Jiang; Chenyang Wang; Zhonghang Yuan; Haoyang Su; Huanjun Kong; Fan Yang; Nanqing Dong (ACL (1), 2025)

Towards Efficient and Intelligent Laser Weeding: Method and Dataset for Weed Stem Detection. - Dingning Liu; Jinzhe Li; Haoyang Su; Bei Cui; Zhihui Wang 001; Qingbo Yuan; Wanli Ouyang; Nanqing Dong (CoRR, 2025)

HuixiangDou2: A Robustly Optimized GraphRAG Approach. - Huanjun Kong; Zhefan Wang; Chenyang Wang; Zhe Ma; Nanqing Dong (CoRR, 2025)

$ tt {zkFL}$zkFL: Zero-Knowledge Proof-Based Gradient Aggregation for Federated Learning. - Zhipeng Wang 009; Nanqing Dong; Jiahao Sun; William Knottenbelt; Yike Guo (IEEE Trans. Big Data, 2025)

AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research. - Renqi Chen; Haoyang Su; Shixiang Tang; Zhenfei Yin; Qi Wu; Hui Li 037; Ye Sun; Nanqing Dong; Wanli Ouyang; Philip Torr 001 (CoRR, 2025)

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing. - Zijie Qiu; Jiaqi Wei; Xiang Zhang 011; Sheng Xu; Kai Zou; Zhi Jin; Zhiqiang Gao; Nanqing Dong; Siqi Sun (CoRR, 2025)

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation. - Zihong Chen; Wanli Jiang; Jinzhe Li; Zhonghang Yuan; Huanjun Kong; Wanli Ouyang; Nanqing Dong (CoRR, 2025)

Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing. - Xiang Zhang 011; Jiaqi Wei; Zijie Qiu; Sheng Xu; Nanqing Dong; Zhiqiang Gao; Siqi Sun (CoRR, 2025)

Dynamic Knowledge Exchange and Dual-diversity Review: Concisely Unleashing the Potential of a Multi-Agent Research Team. - Weilun Yu; Shixiang Tang; Yonggui Huang; Nanqing Dong; Li Fan; Honggang Qi; Wei Liu 123; Xiaoli Diao; Xi Chen 004; Wanli Ouyang (CoRR, 2025)

PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs. - Xinzhe Zheng 001; Hao Du; Fanding Xu; Jinzhe Li; Zhiyuan Liu 001; Wenkang Wang; Tao Chen 003; Wanli Ouyang; Stan Z. Li; Yan Lu 001; Nanqing Dong; Yang Zhang (CoRR, 2025)

From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery. - Jiaqi Wei; Yuejin Yang; Xiang Zhang; Yuhan Chen; Xiang Zhuang; Zhangyang Gao; Dongzhan Zhou; Guangshuai Wang; Zhiqiang Gao; Juntai Cao; Zijie Qiu; Xuming He; et al. (CoRR, 2025)

Intern-S1: A Scientific Multimodal Foundation Model. - Lei Bai 001; Zhongrui Cai; Yuhang Cao; Maosong Cao; Weihan Cao; Chiyu Chen; Haojiong Chen; Kai Chen; Pengcheng Chen; Ying Chen; Yongkang Chen; Yu Cheng; et al. (CoRR, 2025)