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Chenyang Lyu 吕晨阳

Staff Researcher at Alibaba and PhD from Ml-Labs, Dublin City University
Glasnevin, Dublin
Ireland

Email: lyuchenyang.dcu [at] gmail [dot] com
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About

I am currently a Staff Researcher/Tech Lead at the Alibaba AI Business Group, where I head the speech team. Previously, I was a researcher at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), focusing on multilingual and multimodal large language models. I earned my Ph.D. in Machine Learning from Dublin City University's ML-Labs in 2023, following a Bachelor of Engineering from Northeastern University in China in 2018. My research lies primarily in natural language processing, especially the application of large models—including vision-language models—to multilingual and multimodal tasks. I have published over 30 papers at top-tier conferences such as ACL, EMNLP, NeurIPS, and ACM-MM, with my GPT4Video work nominated for the Best Paper Award at ACM-MM 2024. My Google Scholar citations exceed 1,600, with an h-index of 19, and the open-source projects I have led or contributed to have collectively garnered over 4k stars on GitHub. I won two championships and two runner-up prizes in the IWSLT 2025 speech translation competition. I also serve as an area chair, program committee member, shared task organizer, and reviewer for several leading conferences including ICLR, ACL, EMNLP, IJCAI, and ACM-MM. Prior to my current role, I gained extensive research experience in large language models through positions as a research assistant and visiting scholar at Tencent AI Lab, Japan's National Institute of Informatics (NII) and IBM Research-China. My work has been recognized with several awards, including the IWSLT 2025 Speech Translation Competition championship, the ACM-MM 2024 Best Paper nomination, the German DAAD AInet Fellowship, the 2023 Irish AI Young Talent of the Year Award and an SFI PhD Scholarship. Additionally, my research has been featured in media outlets such as Irish national broadcaster RTÉ, Slator, Irish Tech News, and Irish podcasts.

News

2023/06: We have released our Multi-modal Large Language Models named Macaw-LLM!.
2023/07: One paper accepted to the 31st ACM International Conference on Multimedia, ACM-MM 2023!.
2023/06: One paper accepted to the 32nd International Conference on Artificial Neural Networks, ICANN 2023!.
2023/06: Paper New Trends in Machine Translation with Large Language Models accepted to the Symposium on Large Language Models at IJCAI 2023!.
2023/06: Two paper accepted to the Student Research Workshop and SustaiBLP workshop at the 61th Annual Meeting of the Association for Computational Linguistics, ACL 2023!.
2023/05: One paper accepted to the 61th Annual Meeting of the Association for Computational Linguistics, ACL 2023!.
2023/04: New blog for some interesting directions in Machine Translation using Large Language Models: New Trends in Machine Translation using Large Language Models.
2023/04: Our new preprint on investigating Large Language Models (LLMs): Document-Level Machine Translation with Large Language Models is out!
2022/12: “Dialogue-to-Video Retrieval” accepted by ECIR 2023.
2022/09: Our system wins 1st place in FinNLP-2022 (co-located with EMNLP 2022) ERAI shared task!
2022/06: Presented a talk at LREC 2022 Workshop on Financial Narrative Processing, Marseille, France.
2022/05: Presented two posters and a talk at ACL 2022 and Workshop on Insights from Negative Results in NLP, Dublin, Ireland.
2022/04: “Extending the Scope of Out-of-Domain: Examining QA models in multiple subdomains” accepted by ACL 2022 Workshop on Insights from Negative Results in NLP.
2022/02: “Achieving Reliable Human Assessment of Open-Domain Dialogue Systems” accepted by ACL 2022.
2021/11: Presented a talk of our paper at Question Answering session of EMNLP 2021.
2021/08: “Improving Unsupervised Question Answering via Summarization-Informed Question Generation” accepted by EMNLP 2021.
2020/12: Presented a talk of our paper at Sentiment Analysis session of COLING 2020.
2020/10: “Document-Level Sentiment Analysis with User and Product Context” accpeted by COLING 2020.
2020/04: Presented a talk of our paper at ECIR 2020 Workshop on Narrative Extraction from Texts.
2020/02: “Incorporating Context and Knowledge for Better Sentiment Analysis of Narrative Text” accepted by ECIR 2020 Workshop on Narrative Extraction from Texts.

Educational Background

Sep 2019 - Jul 2023, Doctor of Philosophy in Computer Science, ML-Labs, Dublin City University
Oct 2014 - June 2018, Bachelor of Engineering in Computer Software Engineering, Northeastern University

Research Experience

Research Intern, Huawei Noah's Ark Lab, May 2020 - May 2021
Research Intern, IBM Research-China, July 2018 - December 2018

Papers

Graph-Based Video-Language Learning with Multi-Grained Audio-Visual Alignment [PDF][Code][Bibtex]
Chenyang Lyu, Wenxi Li, Tianbo Ji, Longyue Wang, Liting Zhou, Cathal Gurrin, Linyi Yang, Yi Yu, Yvette Graham, Jennifer Foster
In Proceedings of the 31st ACM International Conference on Multimedia, ACM-MM 2023
Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration [PDF][Code][Bibtex]
Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu.
Preprint 2023 (1100+ stars on Github, 300,000 views and discussion on Twitter).
Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering [PDF][Code][Bibtex]
Chenyang Lyu, Tianbo Ji, Yvette Graham, and Jennifer Foster
In Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, ACL 2023
Is a Video worth $n\times n$ Images? A Highly Efficient Approach to Transformer-based Video Question Answering [PDF][Code][Bibtex]
Chenyang Lyu, Tianbo Ji, Yvette Graham, and Jennifer Foster
In Proceedings of The Third Workshop on Simple and Efficient Natural Language Processing, ACL 2023
Exploiting Rich Textual User-Product Context for Improving Personalised Sentiment Analysis [PDF][Code][Bibtex]
Chenyang Lyu, Linyi Yang, Yue Zhang, Yvette Graham, Jennifer Foster
In Findings of the 61th Annual Meeting of the Association for Computational Linguistics, ACL 2023
Gated Multi-Modal Fusion with Cross-Modal Contrastive Learning for Video Question Answering [PDF][Code][Bibtex]
Chenyang Lyu, Wenxi Li, Tianbo Ji, Liting Zhou, Cathal Gurrin
In the 32nd International Conference on Artificial Neural Networks, ICANN 2023
New Trends in Machine Translation with Large Language Models [PDF] [Code][Bibtex]
Chenyang Lyu, Zefeng Du, Jitao Xu, Derek F. Wong, Yitao Duan, Longyue Wang
Symposium on Large Language Models at IJCAI2023
Document-Level Machine Translation with Large Language Models [PDF] [Slides][Code][Bibtex]
Longyue Wang*, Chenyang Lyu*, Tianbo Ji*, Zhirui Zhang*, Dian Yu, Shuming Shi, Zhaopeng Tu
Technical Report 2023
Dialogue-to-Video Retrieval [PDF] [Slides][Code][Bibtex]
Chenyang Lyu, Manh-Duy Nguyen, Van-Tu Ninh, Liting Zhou, Cathal Gurrin, Jennifer Foster
The 45th European Conference on Information Retrieval, ECIR 2023
Extending the Scope of Out-of-Domain: Examining QA models in multiple subdomains [PDF] [Slides][Code][Bibtex]
Chenyang Lyu, Jennifer Foster and Yvette Graham
The 60th Annual Meeting of the Association for Computational Linguistics, ACL 2022, Workshop on Insights from Negative Results in NLP
Achieving Reliable Human Assessment of Open-Domain Dialogue Systems [PDF][Slides][Code][Bibtex]
Tianbo Ji, Yvette Graham, Gareth J. F. Jones, Chenyang Lyu and Qun Liu
The 60th Annual Meeting of the Association for Computational Linguistics, ACL 2022
DCU-Lorcan at FinCausal 2022: Span-based Causality Extraction from Financial Documents using Pre-trained Language Models [PDF][Bibtex]
Chenyang Lyu, Tianbo Ji, Quanwei Sun, Liting Zhou
The 14th Conference on Language Resources and Evaluation, LREC 2022, Proceedings of the 4th Financial Narrative Processing Workshop
Knowledge and Pre-trained Language Models Inside and Out: a deep-dive into datasets and external knowledge [PDF][slides][Bibtex]
Chenyang Lyu
PhD Transfer Report
Improving Unsupervised Question Answering via Summarization-Informed Question Generation [PDF][Slides][Bibtex]
Chenyang Lyu, Lifeng Shang, Yvette Graham, Jennifer Foster, Xin Jiang and Qun Liu
The 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021
Improving Document-Level Sentiment Analysis with User and Product Context [PDF][Slides] [Code][Bibtex]
Chenyang Lyu, Jennifer Foster and Yvette Graham
The 28th International Conference on Computational Linguistics, COLING 2020
Incorporating Context and Knowledge for Better Sentiment Analysis of Narrative Text [PDF][Bibtex]
Chenyang Lyu, Tianbo Ji and Yvette Graham
The 42nd European Conference on Information Retrieval, ECIR 2020, The Third International Workshop on Narrative Extraction from Texts

Teaching Experience

CA-146/297, Introduction to Programming, 2020, Dublin City University, Teaching Assistant
CA-271, Machine Learning, 2022, Dublin City University, Guest Lecturer
CA-168, Digital World, 2022, Dublin City University, Guest Lecturer

Professional Activities

PC Member
- The 45th European Conference on Information Retrieval, ECIR 2023
- The 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
- The 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
- The 3rd Workshop on Financial Technology on the Web in conjunction with The Web Conference 2023, FinWeb 2023
Conference Reviewer
- The 60th Annual Meeting of the Association for Computational Linguistics, ACL 2022
- The 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022
- The 29th International Conference on Computational Linguistics, COLING 2022
- The 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Workshop Reviewer
- EvoNLP: The First Workshop on Ever Evolving NLP, EMNLP 2022
- FinNLP: The Fourth Workshop on Financial Technology and Natural Language Processing, EMNLP 2022
- FinWeb: The 3rd Workshop on Financial Technology on the Web, WWW 2023
Journal Reviewer
- IEEE Transaction on Multimedia, IEEE
- Social Network Analysis and Mining, Springer
- Connection Science, Taylor & Francis
Regular Reviewer
- ACL Rolling Review

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