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I am a fourth-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 also a research intern at Sea AI lab (SAIL). I am mentored by Dr. Tianyu Pang and Dr. Chao Du, and working closely with Dr. Qian Liu, and Dr. Min Lin. My research topics include: (i) foundation models: attention sink of LLMs [ATTRIB @ NeurIPS'2024], and memorization of Diffusion Models [Arxiv'2023]; (ii) AI safety: infectious jailbreak for (multimodal) LLM multi-agents [ICML'2024]; (iii) singing/speech: application of machine learning, e.g. multimodal learning [MM'2022 Oral, TOMM'2024], multi-distribution learning (domain adaptation [ISMIR'2022, TOMM'2024], fairness [MM'2023]), to singing/speech techniques. 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. |
| Foundation Models |
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Xiangming Gu, Tianyu Pang†, Chao Du, Qian Liu, Fengzhuo Zhang, Cunxiao Du, Ye Wang†, Min Lin Annual Conference on Neural Information Processing Systems Workshop on Attributing Model Behavior at Scale (ATTRIB @ NeurIPS'2024), Vancouver, Canada. pdf / code |
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Xiangming Gu, Chao Du†, Tianyu Pang†, Chongxuan Li, Min Lin, Ye Wang† Preprints, 2023. pdf / code |
| AI Safety |
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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'2024), Vienna, Austria. Also in International Conference on Learning Representations Workshop on Large Language Model Agents (LLMAgents @ ICLR'2024). ICML / ICLR workshop / project page / code / video / slides / poster / press |
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Hongfu Liu†, Hengguan Huang, Hao Wang, Xiangming Gu, Ye Wang Annual Conference on Neural Information Processing Systems Safe Generative AI Workshop (SafeGenAI @ NeurIPS'2024), (Oral), Vancouver, Canada. 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'2023), Ottawa, Canada. pdf / code / video / poster |
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Xiangming Gu*, Longshen Ou*, Danielle Ong, Ye Wang† ACM International Conference on Multimedia (MM'2022), (Oral, Top Paper Award), Lisbon, Portugal. 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'2022), Bengaluru, India. pdf / code |
| Bayesian Deep Learning |
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Hengguan Huang†, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, Ye Wang† Annual Conference on Neural Information Processing Systems (NeurIPS'2022), New Orleans, USA. pdf / code / video |
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Wei Wei*, Hengguan Huang*, Xiangming Gu, Hao Wang, Ye Wang† Transactions on Machine Learning Research (TMLR'2022). pdf / code |
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Participant for Global Young Scientists Summit, 2025
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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Conference reviewer for CVPR 2025, ICLR2025, ACL ARR 2024 June/August/October, NeurIPS 2024, MM 2024, ECCV 2024, IJCAI 2024, ICCV 2023, AISTATS 2025/2021
Workshop reviewer for NeurIPS 2024 Workshop on Attributing Model Behavior at Scale, 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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