文本蕴含、因果推理的计算方法方向研究成果：

[1]Chunhua Liu, Shan Jiang, Hainan Yu,Dong Yu. Multi-turn Inference Matching Network for Natural Language Inference. In Proceedings of NLPCC2018 Part II,2018: 131-143. 【Outstanding Paper Award】

[2]Yan Zhao, Lu Liu, Chunhua Liu, Ruoyao Yang, andDong Yu. From Plots to Endings: A Reinforced Pointer Generator for Story Ending Generation. In Proceedings of NLPCC2018 Part I,2018: 51-63.

[3]Chunhua Liu, Yan Zhao, Qingyi Si, Haiou Zhang, Bohan Li,Dong Yu. Multi-Perspective Fusion Network for Commonsense Reading Comprehension.In Proceedings of CCL 2018/NLP-NABD2018, LNAI 11221, pp. 262–274, 2018.

[4]Shan Jiang, Bohan Li, Chunhua Liu, andDong Yu. Knowledge Augmented Inference Network for Natural Language Inference. In Proceedings of CCKS 2018 .pp. 129-135,2018.

[5]Chunhua Liu, Haiou Zhang, Shan Jiang,Dong Yu. DEMN: Distilled-Exposition Enhanced Matching Network for Story Comprehension. In Proceedings of PACLIC2018,2018：385-393.

[6]金天华，姜姗，于东，赵美倩，刘璐.中文句法异构蕴含语块标注和边界识别研究[J].中文信息学报,2019,33(2):17-25.

[7]Dong Yu, Lu Liu, Chen Yu, and Changliang Li. Testing the Reasoning Power for NLI Models with Annotated Multi-perspective Entailment Dataset. In Proceedings ofCCL2019,2019:15-26.

[8]于东,金天华,谢婉莹,张艺,荀恩东.中文文本蕴含类型及语块识别方法研究.软件学报,2020, 31(12):3772−3786.

[9]李博涵,姜姗,刘畅,于东.中文矛盾语块数据集构建和边界识别研究[J].中文信息学报,2020, 34(03):34-43.

[10]Shiya Peng, Lu Liu, Chang Liu,Dong Yu. Exploring Reasoning Schemes: A Dataset for Syllogism Figure Identification. In Proceedings of CLSW2020,2020:445-451.

[11]刘璐，彭诗雅，玉郴，于东.自然语言显式命题自动识别和解析方法[J].中文信息学报,2021,35(2):41-51.

汉语文本可读性测评方面的研究成果：

[1]吴思远，蔡建永，于东，江新.文本可读性的自动分析研究综述[J].中文信息学报,2018,32(12):1-10.

[2]于东,吴思远,耿朝阳,唐玉玲.基于众包标注的语文教材句子难易度评估研究[J].中文信息学报,2020,34(2):16-26.

[3]吴思远,于东,江新*.汉语文本可读性特征体系构建和效度验证[J].世界汉语教学,2020, 34(01):81-97.

[4]Mengxi Que , Yufei Zhang,Dong Yu. RCWI: A Dataset for Chinese ComplexWord Identification.In Proceedings ofCCKS2021,2021:302-307.

[5]唐玉玲,张宇飞,于东.结合深度学习和语言难度特征的句子可读性计算方法[J].中文信息学报,2022,36(02):29-39.

[6]于东,谢婉莹,谷舒豪,冯洋.基于语种关联度课程学习的多语言神经机器翻译[J].计算机科学,2022,49(01):24-30.

[7]Yi Li,Dong Yu, Pengyuan Liu. CLGC: A Corpus for Chinese Literary Grace Evaluation.In Proceedings ofLREC2022,2022:5548-5556.

中文自然语言道德计算方面的研究成果：

[1]王弘睿，刘畅，于东.面向人工智能伦理计算的中文道德词典构建方法研究[J].中文信息学报,2021,35(10):39-47.

[2] 王弘睿,于东.面向机器道德判断任务的细粒度中文道德语义知识库构建[J].中文信息学报,2022, 36(07):59-68.

[3]Shiya Peng, Ying Wang,Dong Yu, Pengyuan Liu. Perception and Cognition Matters: A new light on sentiment analysis task.In Proceedings ofIJCNN2022,2022.

[4]Chunxu Zhao, Pengyuan Liu, Dong Yu. From Polarity to Intensity: Mining Morality from Semantic Space. In Proceedings of the 29th International Conference on Computational Linguistics, 2022:1250-1262.

自然语言处理基础算法方面研究成果：

[1]Haiou Zhang, Hanjun Zhao, Chunhua Liu, andDong Yu. Task-to-Task Transfer Learning with Parameter-Efficient Adapter. In Proceedings of NLPCC2020,2020:391–402.

[2]Ruoyao Yang, Wanying Xie, Chunhua Liu,Dong Yu. BLCU_NLP at SemEval-2019 Task 7: An Inference Chain-based GPT Model for Rumour Evaluation. In Proceedings of Semeval2019,2019:1090-1096.

[3]Yang Feng, Wanying Xie, Shuhao Gu, Chenze Shao, Wen Zhang, Zhengxin Yang,Dong Yu. Modeling Fluency and Faithfulness for Diverse Neural Machine Translation.In Proceedings ofAAAI2020,2020.

[4]Shuhao Gu, Jinchao Zhang, Fandong Meng, Yang Feng, W. Xie, Jie Zhou,Dong Yu. Token-level Adaptive Training for Neural Machine Translation. In Proceedings ofEMNLP2020,2020:1036-1046.

[5]Wanying Xie, Yang Feng, Shuhao Gu,Dong Yu. Importance-based Neuron Allocation for Multilingual Neural Machine Translation. In Proceedings ofACL2021, Volume 1: Long Papers, 2021:5725–5737.

[6]Shike Wang, Wen Zhang, Wenyu Guo,Dong Yu, Pengyuan Liu. Contrastive Learning Based Visual Representation Enhancement for Multimodal Machine Translation.In Proceedings ofIJCNN2022,2022.