Yue Wang
王樾
Staff Research Engineer, Alibaba Group
Singapore
Gmail: wangyue2714
Github: yuewang-cuhk
Google Scholar
About Me
I am a Staff Research Engineer at Alibaba under the leadership of Prof. Steven Hoi. We are building an R&D team focused on code LLMs, reasoning, and agents to push the boundaries of AI-driven development. 🔥We are now actively hiring both full-time and interns in Singapore/China—if you're passionate about advancing AI in these areas with us, please drop me an email!
Previously, I was a Staff Research Scientist at 01.AI, where my work spanned the entire pipeline of pretraining and post‑training, with a focus on enhancing the coding and reasoning capabilities of Yi models. I led the Yi Coder project and oversaw the multimodal post‑training of Aria. Prior to that, I was a Senior Research Scientist at Salesforce AI Research for three years, where I led or co-led 3 major projects: CodeT5, CodeT5+ and CodeRL. Additionally, I was a core contributor to ApexGuru, an applied project aimed at optimizing code efficiency of Salesforce Apex code.
I obtained my Ph.D. degree at The Chinese University of Hong Kong under the supervision of Prof. Michael R. Lyu and Prof. Irwin King in 2020 and received my B.Sci. from Sun Yat-sen University with an outstanding graduate honor in 2016. I interned at Microsoft Research Asia, Tencent AI, Amazon AWS AI, and Salesforce AI Research. My research interest focuses on code LLMs, code understanding and generation, reasoning/agent, and multimodal LLMs.
Publications
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[Preprint'24] Aria-UI: Visual Grounding for GUI Instructions.
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[Technical Report'24] ARIA : An Open Multimodal Native Mixture-of-Experts Model.
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[Preprint'24] HumanEval-V: Evaluating Visual Understanding and Reasoning Abilities of Large Multimodal Models Through Coding Tasks.
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[Preprint'24] AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions.
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[Technical Blog'24] Meet Yi-Coder: A Small but Mighty LLM for Code.
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[Technical Report'24] Yi: Open Foundation Models by 01.AI.
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[Preprint'24] CodeEditorBench: Evaluating Code Editing Capability of Large Language Models.
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[EMNLP'23] CodeT5+: Open Code Large Language Models for Code Understanding and Generation.
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[EMNLP'23] Towards Low-Resource Automatic Program Repair with Meta-Learning and Pretrained Language Models.
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[FSE'23] RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair.The 2023 Symposium on the Foundations of Software Engineering (FSE 2023, Long Paper).
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[arXiv'23] CODETF: One-stop Transformer Library for State-of-the-art Code LLMs.
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[NeurIPS'22] CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningThe 2022 Conference on Neural Information Processing Systems (NeurIPS 2022, Long Paper).
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[EMNLP'22 Findings] Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022 Findings, Long Paper).
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[EMNLP'21] CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and GenerationThe 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021, Long Paper).
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[NAACL'21] Towards Modeling the Style of Translators in Neural Machine TranslationThe 2021 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021, Short Paper).
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[ICASSP'21] Machine Translation Verbosity Control for Automatic DubbingThe 2021 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021, Long Paper).
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[EMNLP'20] VD-BERT: A Unified Vision and Dialog Transformer with BERTThe 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020, Long Paper).
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[EMNLP'20] Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image WordingsThe 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020, Long Paper).
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[ACL'19] Topic-Aware Neural Keyphrase Generation for Social Media LanguageThe 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019, Long Paper).
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[NAACL'19] Microblog Hashtag Generation via Encoding Conversation ContextsThe 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019, Long Paper, Oral).
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[IJCAI'18] Code Completion with Neural Attention and Pointer NetworksThe 2018 International Joint Conference on Artificial Intelligence (IJCAI 2018, Long Paper, Oral).
Working Experience
- Mar 2025-Now: Staff Research Engineer in Alibaba, Singapore.
- Dec 2023-Dec 2024: Staff Research Scientist in 01 AI, Singapore.
- Jan 2021-Dec 2023: Senior Research Scientist in Salesforce AI Research, Singapore.
- Summer 2020: Applied Scientist Intern at Amazon AWS AI Lab, California, USA. Mentor: Prof. Marcello Federico and Hoang Cuong
- Fall 2019: Research Intern at Salesforce AI Research, Singapore. Mentor: Prof. Steven Hoi and Prof. Shafiq Rayhan Joty
- Summer 2018: Research Intern at the NLP Center of Tencent AI Lab, Shenzhen. Mentor: Prof. Jing Li
- Spring 2016: Research Assistant at the Department of Electrical and Computer Engineering in Brigham Young University, Utah, USA. Advisor: Prof. Brent Nelson
- Summer 2015: Research Intern at System Group of Microsoft Research Asia, Beijing. Mentor: Cheng Chen
Selected Awards
- Postgraduate Student Scholarship, CUHK, 2016-2020
- Outstanding Graduate Student, Sun Yat-sen University, 2016
- Third Prize in the 13th Guangdong Collegiate Programming Contest (ACM-ICPC GDCPC), 2015
- National Scholarship, Ministry of Education of the P. R. China, 2013
Academic Service
- Journal Reviewer: TKDE, TIST, TOSEM
- Conference Reviewer: ICML (2024, 2025), ICLR (2024, 2025), NeurIPS (2023), COLM (2024,2025), ACL (2021, 2022, 2025), EMNLP (2019, 2021, 2023)