I am currently a Staff Researcher/Tech Lead at Alibaba Group (ATH), where I lead the Speech and Omni LLM Applied Research 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 spans three main lines: speech and omni models, represented by Marco-Voice for expressive voice cloning and emotional speech synthesis, CVQA for culturally diverse multilingual visual question answering, and GPT4Video for unified video understanding and generation; LLM agents and reliability, including Trust No Tool on agents operating under untrusted tool feedback, Crayotter for traceable long-form video editing, and CoQuIR for quality-aware code retrieval; and multilingual models, including Marco-MoE for efficient sparse multilingual modeling, Marco-LLM for cross-lingual enhancement, and CulturALL for grounded multilingual and multicultural evaluation across 14 languages and 51 regions. My papers have been accepted at top-tier conferences, including NeurIPS, ICML, COLM, ACL, EMNLP, ICASSP, CVPR, and ACM-MM.

My work has received both research and personal recognition. CoQuIR was selected for an ACL 2026 SAC Highlights Award, GPT4Video was nominated for the Best Paper Award at ACM-MM 2024, and I won two championships and two runner-up prizes at the IWSLT 2025 speech translation competition. My open-source projects and contributions have collectively earned 4k+ GitHub stars. I have also received personal honors, including the German DAAD AInet Fellowship, the 2023 Young AI Role Model of the Year award at the Irish AI Awards, and an SFI PhD Scholarship. Individual projects have also received external coverage: CVQA was featured by MBZUAI News, Microsoft Research, and a Microsoft Research podcast; Marco-Voice was covered by Slator; and Marco-LLM was reported by Bloomberg, CNBC, and the South China Morning Post. My broader work and career have also been featured by RTÉ and Irish Tech News, including a podcast interview on LLMs. Before joining Alibaba Group, I held research and visiting positions at Tencent AI Lab, the National Institute of Informatics (NII), and IBM Research-China.

Portrait of Chenyang Lyu
Photo: X / Twitter profile

Research

Speech & Omni Models

Speech, vision, video and audio intelligence across understanding and generation.

LLM Agents and Reliability

Traceable multi-agent workflows, tool-feedback defense and robust evaluation.

Multilingual Models

Efficient model adaptation and culturally grounded intelligence across languages.


Education


Industry & Research Experience

Alibaba Group logo

Staff Researcher / Tech Lead

Alibaba Group · ATH · Speech and Omni LLM Applied Research

Visiting & Research Roles

Tencent logo
Tencent AI LabResearch Assistant / Visiting Scholar
National Institute of Informatics logo
National Institute of InformaticsVisiting Scholar

Research Internships

Huawei logo
Huawei Noah’s Ark LabResearch Intern · 2020–2021
IBM logo
IBM Research-ChinaResearch Intern · 2018

News

🏆 CoQuIR was selected for an ACL 2026 SAC Highlights Award.

🎉 Spurious Rewards Paradox was accepted to ICML 2026.

🎉 ElasticFormer was accepted to CVPR 2026.

🎉 Marco-Voice, LongSpeech and MECap-R1 were accepted to ICASSP 2026.

🎤 Invited industry expert talk on Marco Models at ACM Multimedia Asia 2025.

🏆 Our team secured two championships and two runner-up prizes at IWSLT 2025.

🎉 Four papers on multilingual LLMs and hallucination detection were accepted to ACL 2025.

🎙️ CVQA was featured in a Microsoft Research podcast on culturally aware and linguistically diverse multimodal evaluation.


Selected Publications

* denotes corresponding or equal contribution. See Google Scholar and DBLP for the complete record.

ACL
2026
CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval

Jiahui Geng, Fengyu Cai, Shaobo Cui, Qing Li, Liangwei Chen, Chenyang Lyu, et al.

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics.

COLM
2026
Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling

Fan Jiang, Yu Zhao, Chenyang Lyu, Tianqi Shi, Yichao Du, et al.

Conference on Language Modeling.

CVPR
2026
ElasticFormer: Detecting Objects in HRW Shots via Elastic Computing Vision Transformer

Xiang Li, Wenxi Li, Yuetong Wang, Chenyang Lyu, et al.

IEEE/CVF Conference on Computer Vision and Pattern Recognition.

ICASSP
2026
LongSpeech: A Scalable Benchmark for Transcription, Translation and Understanding in Long Speech

Fei Yang, Xuanfan Ni, Renyi Yang, Jiahui Geng, Qing Li, Chenyang Lyu*, et al.

IEEE International Conference on Acoustics, Speech, and Signal Processing.

ICASSP
2026
Marco-Voice Technical Report

Fengping Tian, Chenyang Lyu, Xuanfan Ni, Haoqin Sun, Qingjuan Li, et al.

IEEE International Conference on Acoustics, Speech, and Signal Processing.

ACM MM
2024
GPT4Video: A Unified Multimodal Large Language Model for Instruction-Followed Understanding and Safety-Aware Generation

Zhanyu Wang, Longyue Wang, Zhen Zhao, Minghao Wu, Chenyang Lyu, et al.

Proceedings of the 32nd ACM International Conference on Multimedia.

NeurIPS
2024
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David Romero*, Chenyang Lyu*, Haryo Akbarianto Wibowo, Teresa Lynn, et al.

NeurIPS Datasets and Benchmarks Track.

View the complete publication list →