赵阳，博士，中国科学院自动化研究所副研究员，硕士生导师。主要研究方向为自然语言处理和机器翻译等，作为负责人和技术骨干承担多个国家自然基金项目、国家重点研发计划子课题和特定领域应用项目等，在领域著名期刊（AI、TASLP、TALLIP等）和会议（AAAI、IJCAI、ACL、EMNLP、COLING等）发表论文30余篇，作为共同作者出版专著《自然语言处理基础与大模型案例与实践》，出版译著《神经机器翻译》，获CCMT 2023最佳论文。 目前担任国际学术期刊 ACM TALLIP 副主编（Associate Editor）。

自然语言处理

1）国家自然基金青年基金项目负责人：融合知识图谱的神经机器翻译方法研究
2）预研项目负责人：文本识别技术
3）科技创新2030-新一代人工智能重大项目子课题负责人：多模态预训练模型的知识增强
4）自动翻译软件项目负责人
5）CCF-腾讯犀牛鸟基金项目负责人

[1] Cong Ma, Yaping Zhan, Yang Zhao, Yu Zhou, and Chengqing Zong. 2023. Vector Quantization Knowledge Transfer For End-to-end text image machine translation. Accepted by ICASSP 2024.
[2] Yang Zhao, Jiajun Zhang, Chengqing Zong. 2023. Transformer: A General Framework from Machine Translation to Others. Machine Intelligence Research 20, 514–538 (2023).
[3] Lu Xiang, Yang Zhao, Junnan Zhu, Yu Zhou, Chengqing Zong. 2023. Zero-shot language extension for dialogue state tracking via pre-trained models and multi-auxiliary-tasks fine-tuning. Knowledge-Based Systems, Volume 259, 2023, 110015.
[4] Cong Ma, Xu Han, Linghui Wu, Yaping Zhang, Yang Zhao, Yu Zhou, and Chengqing Zong. 2023. Modal Contrastive Learning based End-to-End Text Image Machine Translation. IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[5] Cong Ma, Yaping Zhang, Mei Tu, Yang Zhao, Yu Zhou, and Chengqing Zong. 2023. CCIM: Cross-modal Cross-lingual Interactive Image Translation. In EMNLP Findings 2023, pages 4959–4965.
[6] Zixuan Ren, Yang Zhao, and Chengqing Zong. 2023. Towards Informative Open-ended Text Generation with Dynamic Knowledge Triples. In EMNLP Findings 2023, pages 3189–3203.
[7] Zhiyang Zhang, Yaping Zhang, Yupu Liang, Lu Xiang, Yang Zhao, Yu Zhou, and Chengqing Zong. 2023. LayoutDIT: Layout-Aware End-to-End Document Image Translation with Multi-Step Conductive Decoder. In EMNLP Findings 2023, pages 10043–10053.
[8] Rongchuan Tang, Yang Zhao, Chengqing Zong, and Yu Zhou. 2023. Multilingual Knowledge Graph Completion with Language-Sensitive Multi-Graph Attention. In Proceedings of ACL 2023, pages 10508–10519.
[9] Cong Ma, Yaping Zhang, Mei Tu, Yang Zhao, Yu Zhou, Chengqing Zong (2023). E2TIMT: Efficient and Effective Modal Adapter for Text Image Machine Translation. In Proceedings ICDAR 2023.
[10] Cong Ma, Yaping Zhang, Mei Tu, Yang Zhao, Yu Zhou, Chengqing Zong (2023). Multi-Teacher Knowledge Distillation For Text Image Machine Translation. In Proceedings of ICDAR 2023.
[11] Zhiyang Zhang, Yaping Zhang, Lu Xiang, Yang Zhao, Yu Zhou. A Novel Dataset and Benchmark Analysis on Document Image Translation. : In Proceedings of CCMT 2023 (Best paper award).
[12] Yang Zhao, Junnan Zhu, Lu Xiang, Jiajun Zhang, Yu Zhou, Feifei Zhai, Chengqing Zong. 2022. Life-long Learning for Multilingual Neural Machine Translation with Knowledge Distillation. arXiv preprint arXiv:2212.02800.
[13] Cong Ma, Yaping Zhang, Mei Tu, Xu Han, Linghui Wu, Yang Zhao, Yu Zhou. 2022. Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task. In Proceedings ICPR 2022.
[14] Mei Li, Lu Xiang, Xiaomian Kang, Yang Zhao, Yu Zhou, Chengqing Zong (2021). Medical Term and Status Generation From Chinese Clinical Dialogue With Multi-Granularity Transformer. IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 3362-3374, 2021.
[15] Lu Xiang, Junnan Zhu, Yang Zhao, Yu Zhou, Chengqing Zong (2021). Robust cross-lingual task-oriented dialogue. ACM Transactions on Asian and Low-Resource Language Information Processing, 20, 6, Article 93 (November 2021)
[16] Xiaomian Kang, Yang Zhao, Jiajun Zhang, Chengqing Zong (2021). Enhancing Lexical Translation Consistency for Document-Level Neural Machine Translation. ACM Transactions on Asian and Low-Resource Language Information Processing, 21, 3, Article 59 (May 2022).
[17] Hao He, Qian Wang, Zhipeng Yu, Yang Zhao, Jiajun Zhang, Chengqing Zong (2021). Synchronous interactive decoding for multilingual neural machine translation. In Proceedings of AAAA 2021, 35(14), 12981-12988.
[18] Lu Xiang, Yang Zhao, Junnan Zhu, Yu Zhou, Chengqing Zong (2021). Zero-Shot Deployment for Cross-Lingual Dialogue System. In Proceedings of NLPCC 2021.
[19] Jiajun Zhang, Long Zhou, Yang Zhao, Chengqing Zong. 2020. Synchronous bidirectional inference for neural sequence generation. Artificial Intelligence, Volume 281, 2020, 103234.
[20] Yang Zhao, Jiajun Zhang, Yu Zhou, Chengqing Zong. 2020. Knowledge graphs enhanced neural machine translation. In Proceedings of IJCAI 2020,  4039–4045.
[21] Yang Zhao, Lu Xiang, Junnan Zhu, Jiajun Zhang, Yu Zhou, Chengqing Zong. 2020. Knowledge graph enhanced neural machine translation via multi-task learning on sub-entity granularity. In Proceedings of COLING 2020, pages 4495–4505.
[22] Xiaomian Kang, Yang Zhao, Jiajun Zhang, Chengqing Zong. 2020. Dynamic context selection for document-level neural machine translation via reinforcement learning. In Proceedings of EMNLP 2020, pages 2242–2254.
[23] Long Zhou, Jiajun Zhang, Yang Zhao, Chengqing Zong. 2020. Non-autoregressive neural machine translation with distortion model. In  Proceedings of NLPCC 2020..
[24] Yang Zhao, Jiajun Zhang, Chengqing Zong, Zhongjun He, Hua Wu. 2019. Addressing the under-translation problem from the entropy perspective. In Proceedings of AAAI 2019, 33(01), 451-458.
[25] Jiajun Zhang, Yang Zhao, Haoran Li, Chengqing Zong. 2018. Attention with sparsity regularization for neural machine translation and summarization. IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 3, pp. 507-518
[26] Yang Zhao, Jiajun Zhang, Zhongjun He, Chengqing Zong, Hua Wu. 2018. Addressing troublesome words in neural machine translation. In Proceedings of EMNLP 2018, pages 391–400.
[27] Yang Zhao, Yining Wang, Jiajun Zhang, Chengqing Zong. 2018. Phrase table as recommendation memory for neural machine translation. In Proceedings of IJCAI 2018, pages 4609–4615.
[28] Yang Zhao, Jiajun Zhang and Chengqing Zong. 2018. Exploiting pre-ordering for neural machine translation. In Proceedings of lrec 2018, pages 893–899.
[29] Yuchen Liu, Long Zhou, Yining Wang, Yang Zhao, Jiajun Zhang, and Chengqing Zong. 2018. A comparable study on model averaging, ensembling and reranking in nmt. In NLPCC 2018.

CCMT 2019最佳论文
中国科学院大学校级研究生优秀课程

(1) 赵阳; 马聪; 张亚萍; 周玉; 基于多任务训练的端到端图像文本翻译方法、系统、装置，2021-3-23, 中国，CN20211
0306816.
(2) 赵阳; 张家俊; 周玉; 宗成庆; 基于知识图谱的神经机器翻译方法、装置、设备及介质，2021-10-14, 中国，CN2021
11199951.2.
[3] 张家俊;李鑫;赵阳;宗成庆; 对比学习模型的训练方法及装置、汉字表示方法及装置. CN202210581040.4
[4] 张家俊;赵阳;王亦宁;宗成庆; 基于神经机器翻译系统的单词预测方法及系统.CN201611209226.8