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, and Dong 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-NABD 2018, LNAI 11221, pp. 262–274, 2018.

 [4]Shan Jiang, Bohan Li, Chunhua Liu, and Dong 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 of CCL2019, 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 Complex Word Identification.  In Proceedings of CCKS2021,2021:302-307.

[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 of LREC2022, 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 of IJCNN2022, 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, and Dong 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 of AAAI2020, 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 of EMNLP2020, 2020:1036-1046.

[5] Wanying Xie, Yang Feng, Shuhao Gu, Dong Yu. Importance-based Neuron Allocation for Multilingual Neural Machine Translation. In Proceedings of ACL2021, 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 of IJCNN2022, 2022.