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I am a final-year Ph.D. candidate from NUS Sound and Music Computing Lab, where I am supervised by Prof. Ye Wang. I am affiliated to Integrative Sciences and Engineering Programme and School of Computing at National University of Singapore. Before that, I obtained my B.E. degree of Electronic Engineering and B.S. degree of Finance at Tsinghua University in 2021. I am a student researcher at Google Deepmind (GDM) in London, United Kingdom, where I am hosted by Dr. Petar VeliÄkoviÄ and Dr. Larisa Markeeva. I was a research intern at Sea AI lab (SAIL), where I was mentored by Dr. Tianyu Pang and Dr. Chao Du, and worked closely with Dr. Qian Liu, and Dr. Min Lin. Currently, my main research focus is understanding, advancing and safety deployment of generative models. During my earlier Ph.D. journey, I have done some work on bayesian deep learning, and application of machine learning to singing/speech domain. Email / CV / Google Scholar / Openreview / Linkedin / Twitter / Github |
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| * denotes equal contribution, † denotes correspondence. Please see my CV or Google Scholar for full list. |
| Understanding Generative Models |
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Xiangming Gu, Tianyu Pang†, Chao Du, Qian Liu, Fengzhuo Zhang, Cunxiao Du, Ye Wang†, Min Lin International Conference on Learning Representations (ICLR), Singapore, Singapore, 2025. (Spotlight) Also in Annual Conference on Neural Information Processing Systems Workshop on Attributing Model Behavior at Scale (ATTRIB @ NeurIPS), Vancouver, Canada, 2024. (Oral) pdf / code / video / long talk / slides / poster |
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Xiangming Gu, Chao Du†, Tianyu Pang†, Chongxuan Li, Min Lin, Ye Wang† Transactions on Machine Learning Research (TMLR), 2025. pdf / code |
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Federico Barbero*†, Ćlvaro Arroyo*, Xiangming Gu, Christos Perivolaropoulos, Michael Bronstein, Petar VeliÄkoviÄ, Razvan Pascanu Preprints, 2025. |
| Advancing Generative Models |
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Tongyao Zhu, Qian Liu†, Haonan Wang, Shiqi Chen, Xiangming Gu, Tianyu Pang, Min-Yen Kan International Conference on Learning Representations Workshop on Open Science for Foundation Models (SCI-FM @ ICLR), Singapore, Singapore, 2025. pdf / code |
| Safety of Generative Models |
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Xiangming Gu*, Xiaosen Zheng*, Tianyu Pang*†, Chao Du, Qian Liu, Ye Wang†, Jing Jiang†, Min Lin International Conference on Machine Learning (ICML), Vienna, Austria, 2024. Also in International Conference on Learning Representations Workshop on Large Language Model Agents (LLMAgents @ ICLR), Vienna, Austria, 2024. pdf / project page / code / video / slides / ICML poster / GYSS poster / press |
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Hongfu Liu†, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang International Conference on Learning Representations (ICLR), Singapore, Singapore, 2025. Also in Annual Conference on Neural Information Processing Systems Safe Generative AI Workshop (SafeGenAI @ NeurIPS), Vancouver, Canada, 2024. (Oral) pdf / code |
| Speech and Singing |
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Xiangming Gu, Longshen Ou, Wei Zeng, Jianan Zhang, Nicholas Wong, Ye Wang† ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2024. pdf / code / data |
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Xiangming Gu, Wei Zeng, Ye Wang† ACM International Conference on Multimedia (MM), Ottawa, Canada, 2023. pdf / code / video / poster |
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Xiangming Gu*, Longshen Ou*, Danielle Ong, Ye Wang† ACM International Conference on Multimedia (MM), Lisbon, Portugal, 2022. (Oral, Top Paper Award) pdf / appendix / project page / code / data / video / press |
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Longshen Ou*, Xiangming Gu*, Ye Wang† International Society for Music Information Retrieval Conference (ISMIR), Bengaluru, India, 2022. pdf / code |
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Dean's Graduate Research Excellence Award, National University of Singapore, 2024
Research Incentive Award, National University of Singapore, 2023 Research Achievement Award, National University of Singapore, 2022 MM'22 Top Paper Award, Association for Computing Machinery, 2022 MM'22 Student Travel Grant, Association for Computing Machinery, 2022 President's Graduate Fellowship, National University of Singapore, 2021 Visiting Undergraduate Student Scholarship, Tsinghua University, 2020 Tsinghua's Friend- Zheng Geru Scholarship, Tsinghua University, 2018 |
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ASAP Seminar Series, invited talk on When Attention Sink Emerges in Language Models: An Empirical View, 2025
Singapore Alignment Workshop, poster presentation on Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast, 2025 NUS Research Week Open House, invited talk on On the Interpretability and Safety of Generative Models , 2025 Global Young Scientists Summit, poster presentation on Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast, 2025 |
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Conference reviewer for NeurIPS 2025/2024, ICML 2025, ICLR 2025, CVPR 2025, ICCV 2025/2023, ECCV 2024, ACL ARR 2025/2024, MM 2025/2024, IJCAI 2024, AISTATS 2025/2021
Workshop reviewer for (i) ICLR 2025 Workshop on Deep Generative Model in Machine Learning: Theory, Principle and Efficacy, (ii) NeurIPS 2024 Workshop on Attributing Model Behavior at Scale, (iii) NeurIPS 2024 Safe Generative AI Workshop Journal reviewer for TOMM, TASLP, RA-L |
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Teaching Assistant, CS4347/CS5647, Sound and Music Computing, Fall 2024
Teaching Assistant, CS6212, Topics in Media, Spring 2024 Teaching Assistant, CS5242, Neural Networks and Deep Learning, Spring 2023 Teaching Assistant, CS3244, Machine Learning, Fall 2022 Teaching Assistant, CS4243, Computer Vision and Pattern Recognition, Spring 2022 |
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