Yingce Xia

Preprints

• Microsoft Research AI4Science, Microsoft Azure Quantum, The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4 (opens in new tab), 2023. (Contribute to the drug discovery chapter).

Journals

• Kehan Wu, Yingce Xia, Pan Deng, Renhe Liu, Yuan Zhang, Han Guo, Yumeng Cui, Qizhi Pei, Lijun Wu, Shufang Xie, Si Chen, Xi Lu, Song Hu, Jinzhi Wu, Chi-Kin Chan, Shawn Chen, Liangliang Zhou, Nenghai Yu, Enhong Chen, Haiguang Liu, Jinjiang Guo, Tao Qin, Tie-Yan Liu, Target-aware Molecule Generation for Drug Design Using a Chemical Language Model (opens in new tab), Nature Communications, 2024, [Keynote by Chris Bishop, start at 11:25] (opens in new tab)[Technical blog] (opens in new tab)
• Shang Zhu, Bichlien H. Nguyen, Yingce Xia, Kali Frost, Shufang Xie, Venkatasubramanian Viswanathan, and Jake Smith, Improved Environmental Chemistry Property Prediction of Molecules with Graph Machine Learning, Green Chemistry, 2023. [ChemArxiv (opens in new tab)]
• Qizhi Pei, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Haiguang Liu, Rui Yan, Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction, Briefings in Bioinformatics 2023
• Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Wengang Zhou, Tao Qin, Houqiang Li, Haiguang Liu, Tie-Yan Liu, Direct Molecular Conformation Generation (opens in new tab), Transactions on Machine Learning Research (TMLR) 2022. [code (opens in new tab)]
• Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu, BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining. Briefings in Bioinformatics, 2022
• Jiacheng Lin, Lijun Wu, Jinhua Zhu, Xiaobo Liang, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu, R^2-DDI: Relation-aware Feature Refinement for Drug-Drug Interaction Prediction. Briefings in Bioinformatics, 2022. [code (opens in new tab)]
• Lijun Wu, Chengcan Yin, Jinhua Zhu, Zhen Wu, Liang He, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu, SPRoBERTa: Protein Embedding Learning with Local Fragment Modeling. Briefings in Bioinformatics, 2022
• Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Tao Qin, Tie-Yan Liu, Discovering Drug-Target Interaction Knowledge from Biomedical Literature (opens in new tab), Bioinformatics, 2022. [code (opens in new tab)]
• Jinhua Zhu, Yingce Xia, Lijun Wu, Jiajun Deng, Wengang Zhou, Tao Qin, Tie-Yan Liu, Houqiang Li, Masked Contrastive Representation Learning for Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022. [arXiv] (opens in new tab) [code (opens in new tab)]
• Yang Fan, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie, Tao Qin, Back Translation for Molecule Generation (opens in new tab), Bioinformatics, 2021. [code (opens in new tab)]
• Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu, Dual Learning: Theoretical Study and an Algorithmic Extension (opens in new tab), SN Computer Science, 2021.
• Jianxin Lin, Yingce Xia, Sen Liu, Shuxin Zhao, Zhibo Chen, ZstGAN: An Adversarial Approach for Unsupervised Zero-Shot Image-to-Image Translation (opens in new tab), Neurocomputing 2021.
• Xueqing Wu, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie, Tao Qin, A Study of BERT for Context-Aware Neural Machine Translation, Springer journal Machine Learning, ACML journal track, 2021 [code (opens in new tab)]
• Shufang Xie, Yingce Xia, Lijun Wu, Yiqing Huang, Yang Fan, Tao Qin, End-to-End Entity-Aware Neural Machine Translation, Springer journal Machine Learning, ACML journal track, 2021
• Yang Fan, Fei Tian, Yingce Xia, Tao Qin, Xiangyang Li, and Tie-Yan Liu, Searching Better Architectures for Neural Machine Translation (opens in new tab), IEEE Transactions on Audio, Speech and Language Processing, 2020.
• Jianxin Lin, Zhibo Chen, Yingce Xia, Sen Liu, Tao Qin, Jiebo Luo, Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation (opens in new tab), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
• Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Enhong Chen, Tie-Yan Liu, Semi-supervised Neural Machine Translation via Marginal Distribution Estimation (opens in new tab), IEEE Transactions on Audio, Speech and Language Processing, 2019
• Yingce Xia, Tao Qin, Wenkui Ding, Haifang Li, Xu-Dong Zhang, Nenghai Yu and Tie-Yan Liu, Finite Budget Analysis of Multi-armed Bandit Problems (opens in new tab), (Neurocomputing 2017).

Conferences

• Qizhi Pei, Lijun Wu, Zhenyu He, Jinhua Zhu, Yingce Xia, Shufang Xie, Rui Yan, Exploiting Pre-trained Models for Drug Target Affinity Prediction with Nearest Neighbors, the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024)
• Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan, FABind: Fast and Accurate Protein-Ligand Binding, 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023)
• Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu, Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design, 29th ACM SIGKDD conference on knowledge discovery and data mining, (KDD-2023).
• Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu, Dual-view Molecule Pre-training (opens in new tab), 29th ACM SIGKDD conference on knowledge discovery and data mining, (KDD-2023) . [code (opens in new tab)]
• Qizhi Pei, Wei Zhang, Jinhua Zhu, Kehan Wu, Kaiyuan Gao, Lijun Wu, Yingce Xia, Rui Yan, BioT5: Enriching Cross-model Integration in Biology with Chemical Knowledge and Natural Language Associations, the 2023 Conference on Empirical Methods in Natural Language Processing, (EMNLP-2023)
• Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang and Tie-Yan Liu, MolXPT: Wrapping Molecules with Text for Generative Pre-training (opens in new tab) (short paper), the 61st Annual Meeting of the Association for Computational Linguistics, (ACL-2023).
• Griffin Adams, Bichlien H. Nguyen, Jake Allen Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yusan-Jyue Chen, Tristan Naumann and Noémie Elhadad, What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization, the 61st Annual Meeting of the Association for Computational Linguistics, (ACL-2023).
• Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu, Retrosynthetic Planning with Dual Value Networks, Fortieth International Conference on Machine Learning, (ICML-2023).
• Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu, De Novo Molecular Generation via Connection-aware Motif Mining (opens in new tab), 11th International Conference on Learning Representations, (ICLR-2023).
• Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu, O-GNN: incorporating ring priors into molecular modeling (opens in new tab), 11th International Conference on Learning Representations, (ICLR-2023).
• Jinpeng Li, Yingce Xia, Xin Cheng, Dongyan Zhao, Rui Yan, Learning Disentangled Representations via Domain Adaption for Dialogue Summarization, the Web Conference 2023 (WWW-2023).
• Shufang Xie, Rui Yan, Junliang Guo, Yingce Xia, Lijun Wu, Tao Qin, Retrosynthesis Prediction with Local Template Retrieval (opens in new tab), in Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023).
• Siun Kim, Jung-Hyun Won, David Lee, Renqian Luo, Lijun Wu, Yingce Xia, Tao Qin, Howard Lee, Revisiting Machine-Learning based Drug Repurposing: Drug Indications Are Not a Right Prediction Target, in the Conference on Health, Inference, and Learning, (CHIL-2023).
• Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li and Tie-Yan Liu. Unified 2D and 3D Pre-Training of Molecular Representations, the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• Shufang Xie, Peng Han, Yingce Xia, Lijun Wu, Tao Qin, Chenjuan Guo, Bin Yang and Rui Yan. RetroGraph: Retrosynthetic Planning with Graph Search, the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
• Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Rui Yan, Tie-Yan Liu, Target-Side Data Augmentation for Sequence Generation (opens in new tab), the Tenth International Conference on Learning Representations. (ICLR-22)
• Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian, DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation, in 36th AAAI Conference on Artificial Intelligence (AAAI-22)
• Jinpeng Li, Yingce Xia, Rui Yan, Hongda Sun, Dongyan Zhao, Tie-Yan Liu, Stylized Dialogue Generation with Multi-Pass Dual Learning (opens in new tab), in 35th Conference on Neural Information Processing Systems (NeurIPS-21)
• Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu, Temporally Correlated Task Scheduling for Sequence Learning (opens in new tab), In 38th International Conference on Machine Learning (ICML-21). [code-MT (opens in new tab)] [code-finance (opens in new tab)]
• Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu, IOT: Instance-wise Layer Reordering for Transformer Structures (opens in new tab), in The Ninth International Conference on Learning Representations (ICLR-2021)
• Zhen Wu, Lijun Wu, Qi Meng, Yingce Xia, Shufang Xie, Tao Qin, Xinyu Dai and Tie-Yan Liu, UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost (opens in new tab), in The 2021 Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL-2021)
• Yang Fan, Yingce Xia, Lijun Wu, Shufang Xie, Weiqing Liu, Jiang Bian, Xiangyang Li, Tao Qin, Learning to Reweight with Deep Interactions (opens in new tab), 35th AAAI Conference on Artificial Intelligence (AAAI-21)
• Xueqing Wu, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie and Tao Qin, mixSeq: A Simple Data Augmentation Method for Neural Machine Translation, International Conference on Spoken Language Translation, 2021 (IWSLT-21)
• Jianxin Lin, Yingxue Pang, Yingce Xia, Zhibo Chen, Jiebo Luo, TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images (opens in new tab), 2020 European Conference on Computer Vision (ECCV-20, Spotlight) [code (opens in new tab)]
• Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li and Tie-Yan Liu, Incorporating BERT into Neural Machine Translation (opens in new tab), 8th International Conference on Learning Representations (ICLR-20) [code (opens in new tab)]
• Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Tao Qin, Jian-Huang Lai and Tie-Yan Liu, Sequence Generation with Mixed Representations, 37th International Conference on Machine Learning (ICML-20)
• Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai and Tie-Yan Liu, Transductive Ensemble Learning for Neural Machine Translation (opens in new tab), 34th AAAI Conference on Artificial Intelligence (AAAI-20)
• Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu, Dual Learning: Theoretical Study and an Algorithmic Extension (opens in new tab), the 12th Asian Conference on Machine Learning (ACML-20).
• Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, ChengXiang Zhai and Tie-Yan Liu, Neural Machine Translation with Soft Prototype (opens in new tab), 33rd Conference on Neural Information Processing Systems (NeurIPS-19)
• Lijun Wu, Yiren Wang, Yingce Xia, Tao Qin, Jianhuang Lai, and Tie-Yan Liu, Exploiting Monolingual Data at Scale for Neural Machine Translation (opens in new tab), 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP-19)
• Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, and Tie-Yan Liu, Multilingual Neural Machine Translation with Language Clustering (opens in new tab), 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP-19)
• Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, and Tie-Yan Liu, Microsoft Research Asia’s Systems for WMT19 (opens in new tab), Fourth Conference on Machine Translation (WMT-2019)
• Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin and Tie-Yan Liu, Depth Growing for Neural Machine Translation (opens in new tab), (short paper), In 57th Annual Meeting of the Association for Computational Linguistics (ACL-19). [code (opens in new tab)]
• Jinhua Zhu, Fei Gao, Lijun Wu, Yingce Xia, Tao Qin, Wengang Zhou, Xueqi Cheng, and Tie-Yan Liu, Soft Contextual Data Augmentation for Neural Machine Translation (opens in new tab), (short paper), In 57th Annual Meeting of the Association for Computational Linguistics (ACL-19).
• Jianxin Lin, Yingce Xia, Tao Qin, Yijun Wang, Zhibo Chen, Image-to-Image Translation with Multi-Path Consistency Regularization (opens in new tab), In 28th International Joint Conference on Artificial Intelligence (IJCAI-19).
• Tianyu He, Yingce Xia, Jianxin Lin, Xu Tan, Di He, Tao Qin, Zhibo Chen, Deliberation Learning for Image-to-Image Translation (opens in new tab), In 28th International Joint Conference on Artificial Intelligence (IJCAI-19).
• Yiren Wang, Yingce Xia, Tianyu He, Fei Tian, Tao Qin, ChengXiang Zhai and Tie-Yan Liu, Multi-Agent Dual Learning (opens in new tab), In 7th International Conference on Learning Representations (ICLR-19).
• Yingce Xia, Tianyu He, Xu Tan, Fei Tian, Di He and Tao Qin, Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder (opens in new tab), In 33rd AAAI Conference on Artificial Intelligence (AAAI-19).
• Yingce Xia, Xu Tan, Fei Tian, Tao Qin, Nenghai Yu and Tie-Yan Liu, Model-Level Dual Learning (opens in new tab), 35th International Conference on Machine Learning (ICML-18).
• Tianyu He, Xu Tan, Yingce Xia, Di He, Tao Qin, Zhibo Chen, and Tie-Yan Liu, Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation (opens in new tab), In 32nd Conference on Neural Information Processing Systems (NeurIPS 2018).
• Lijun Wu, Fei Tian, Yingce Xia, Tao Qin, Jianhuang Lai, and Tie-Yan Liu, Learning to Teach with Dynamic Loss Functions (opens in new tab),  In 32nd Conference on Neural Information Processing Systems (NeurIPS 2018).
• Hany Hassan, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt, William Lewis, Mu Li, Shujie Liu, Tie-Yan Liu, Renqian Luo, Arul Menezes, Tao Qin, Frank Seide, Xu Tan, Fei Tian, Lijun Wu, Shuangzhi Wu, Yingce Xia, Dongdong Zhang, Zhirui Zhang, Ming Zhou, Achieving Human Parity on Automatic Chinese to English News Translation (opens in new tab), arXiv 2018.
• Jianxin Lin, Yingce Xia, Tao Qin, Zhibo Chen and Tie-Yan Liu, Conditional Image-to-Image Translation (opens in new tab), IEEE Conference on Computer Vision and Pattern Recognition (CVPR-18).
• Haifang Li, Yingce Xia and Wensheng Zhang, Finite Sample Analysis of LSTD with Random Projections and Eligibility Trace (opens in new tab), 27th International Joint Conference on Artificial Intelligence (IJCAI-18).
• Yijun Wang, Yingce Xia, Li Zhao, Jiang Bian, Tao Qin, Guiquan Liu and Tie-Yan Liu, Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization (opens in new tab), In 32nd AAAI Conference on Artificial Intelligence (AAAI-18).
• Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jianhuang Lai and Tie-Yan Liu, Adversarial Neural Machine Translation (opens in new tab), In 10th Asian Conference on Machine Learning (ACML-18).
• Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu and Tie-Yan Liu, Deliberation Networks: Sequence Generation Beyond One-Pass Decoding (opens in new tab), In 31th Conference on Neural Information Processing Systems (NIPS-17).
• Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang and Tie-Yan Liu, Decoding with Value Networks for Neural Machine Translation (opens in new tab), In 31th Conference on Neural Information Processing Systems (NIPS-17).
• Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu and Tie-Yan Liu, Dual Supervised Learning (opens in new tab), In 34th International Conference on Machine Learning, (ICML-2017). [code (opens in new tab)]
• Yingce Xia, Jiang Bian, Tao Qin, Nenghai Yu and Tie-Yan Liu, Dual Inference for Machine Learning (opens in new tab), In 26th International Joint Conference on Artificial Intelligence, (IJCAI-2017).
• Yingce Xia, Fei Tian, Tao Qin, Nenghai Yu and Tie-Yan Liu, Sequence Generation with Target Attention (opens in new tab), In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2017, (ECML/PKDD-2017).
• Haifang Li, Yingce Xia, Infinitely Many-Armed Bandits with Budget Constraints (opens in new tab), In 31st AAAI Conference on Artificial Intelligence (AAAI-17).
• Di He*, Yingce Xia*, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu and Wei-Ying Ma, Dual Learning for Machine Translation (opens in new tab), In 30th Conference on Neural Information Processing Systems (NIPS-16). (“*” indicates equal contribution.)
• Yingce Xia, Tao Qin, Weidong Ma, Nenghai Yu and Tie-Yan Liu, Budgeted Multi-armed Bandits with Multiple Plays (opens in new tab), In 25th International Joint Conference on Artificial Intelligence (IJCAI-16).
• Yingce Xia, Tao Qin, Nenghai Yu and Tie-Yan Liu, Best Action Selection in a Stochastic Environment (opens in new tab),In 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16).
• Yingce Xia, Wenkui Ding, Xu-Dong Zhang, Nenghai Yu and Tao Qin, Budgeted Bandit Problems with Continuous Random Costs (opens in new tab), In 7th Asian Conference on Machine Learning (ACML-15).
• Yingce Xia, Haifang Li, Tao Qin, Nenghai Yu and Tie-Yan Liu, Thompson Sampling for Budgeted Multi-armed Bandits (opens in new tab), In 24th International Joint Conference on Artificial Intelligence (IJCAI-15).
• Long Tran–Thanh, Yingce Xia, Tao Qin and Nicholas R. Jennings, Efficient Algorithms with Performance Guarantees for the Stochastic Multiple-Choice Knapsack Problem (opens in new tab), In 24th International Joint Conference on Artificial Intelligence (IJCAI-15).
• Yingce Xia, Tao Qin, Nenghai Yu and Tie-Yan Liu, Incentivizing High-quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium (opens in new tab), In 28th AAAI Conference on Artificial Intelligence (AAAI-14).

Workshop

• Boning Li, Yingce Xia, Shufang Xie, Lijun Wu and Tao Qin, Distance-Enhanced Graph Neural Network for Link Prediction (opens in new tab), in the 2021 ICML Workshop on Computational Biology