| 2026 | ACL | Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains. | Zhonghang Yuan, Zhefan Wang, Fang Hu, Zihong Chen, Jinzhe Li, Gang Li, Jie Ying, Huanjun Kong, Songyang Zhang, Nanqing Dong |
| 2025 | AAAI | 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 |
| 2025 | ACL | 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, Jinzhe Li, Biqing Qi, Qi Wu, Hui Li, Wanli Ouyang, Philip Torr, Bowen Zhou, Nanqing Dong |
| 2025 | ACL | ROGRAG: A Robustly Optimized GraphRAG Framework. | Zhefan Wang, Huanjun Kong, Jie Ying, Wanli Ouyang, Nanqing Dong |
| 2025 | ACL | 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 |
| 2025 | EMNLP | Biology-Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models. | Haonan He, Yuchen Ren, Yining Tang, Ziyang Xu, Junxian Li, Minghao Yang, Di Zhang, Dong Yuan, Tao Chen, Shufei Zhang, Yuqiang Li, Nanqing Dong, Wanli Ouyang, Dongzhan Zhou, Peng Ye |
| 2025 | ICML | Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing. | Xiang Zhang, Jiaqi Wei, Zijie Qiu, Sheng Xu, Nanqing Dong, Zhiqiang Gao, Siqi Sun |
| 2025 | ICML | Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing. | Zijie Qiu, Jiaqi Wei, Xiang Zhang, Sheng Xu, Kai Zou, Zhi Jin, Zhiqiang Gao, Nanqing Dong, Siqi Sun |
| 2024 | AAAI | ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing. | Zhi Jin, Sheng Xu, Xiang Zhang, Tianze Ling, Nanqing Dong, Wanli Ouyang, Zhiqiang Gao, Cheng Chang, Siqi Sun |
| 2024 | IJCAI | 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 |
| 2024 | IJCAI | Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method. | Weizhen Liu, Ao Li, Ze Wu, Yue Li, Baobin Ge, Guangyu Lan, Shilin Chen, Minghe Li, Yunfei Liu, Xiaohui Yuan, Nanqing Dong |
| 2024 | IJCAI | 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 |
| 2022 | CVPR | Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity. | Nanqing Dong, Jiayi Wang, Irina Voiculescu |
| 2022 | ICIP | Computationally-Efficient Vision Transformer for Medical Image Semantic Segmentation Via Dual Pseudo-Label Supervision. | Ziyang Wang, Nanqing Dong, Irina Voiculescu |
| 2022 | IJCAI | Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images. | Nanqing Dong, Matteo Maggioni, Yongxin Yang, Eduardo Prez-Pellitero, Ales Leonardis, Steven McDonagh |
| 2022 | MICCAI | Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images. | Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu |
| 2021 | BMVC | Quantum Unsupervised Domain Adaptation: Does Entanglement Help? | Nanqing Dong, Michael C. Kampffmeyer, Irina Voiculescu |
| 2021 | MICCAI | Federated Contrastive Learning for Decentralized Unlabeled Medical Images. | Nanqing Dong, Irina Voiculescu |
| 2020 | ECAI | Adversarial Domain Adaptation Being Aware of Class Relationships. | Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing |
| 2019 | ICLR | Toward Understanding the Impact of Staleness in Distributed Machine Learning. | Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing |
| 2019 | MICCAI | Neural Architecture Search for Adversarial Medical Image Segmentation. | Nanqing Dong, Min Xu, Xiaodan Liang, Yiliang Jiang, Wei Dai, Eric P. Xing |
| 2018 | BMVC | Few-Shot Semantic Segmentation with Prototype Learning. | Nanqing Dong, Eric P. Xing |
| 2018 | MICCAI | SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays. | Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P. Xing |
| 2018 | MICCAI | Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. | Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing |
| 2018 | MICCAI | 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, Eric P. Xing |