Xiangming Gu

I am a final-year Ph.D. candidate from National University of Singapore, supervised by Prof. Ye Wang. I earned my B.E. degree of Electronic Engineering and B.S. degree of Finance from Tsinghua University in 2021.

I am a student researcher at Google Deepmind in London, United Kingdom, where I am hosted by Petar Veliฤkoviฤ‡ and Larisa Markeeva. I was lucky to be mentored by Tianyu Pang and Chao Du at Sea AI lab (SAIL), Singapore, where I also worked closely with Qian Liu and Min Lin.

My current research focus is to understand, advance and safely deploy generative models and agents. One of my long-term goals is to use test-time-scaling/agents for challenging problems, such as scientific discovery.

I am looking for full-time research scientist/engineer positions, please contact me if you are interested in my research.

Email  /  CV  /  Google Scholar  /  Openreview  /  Linkedin  /  Twitter  /  Github

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News
  • [2025.10]: I was glad to give a final presentation to wrap up my student researcher at Google Deepmind: Looking into LLMs: From Tokens to Solutions and I will continue my work in Singapore Google office as a part-time student researcher!
  • [2025.10]: We released a technical report titled Extracting Alignment Data in Open Models!
  • [2025.09]: One paper got accepted to Advances in Neural Information Processing Systems (NeurIPS'2025)!
  • [2025.07]: One paper got accepted to Conference on Language Modeling (COLM'2025)!
  • [2025.06]: I was glad to give a talk about Understanding Attention Sink in (Large) Language Models in the team of Deep Learning: Agent Frontier at Google Deepmind.
  • [2025.05]: I was invited to give a talk on When Attention Sink Emerges in Language Models: An Empirical View by ASAP Seminar Series!
  • [2025.05]: I joined Google Deepmind (GDM) as a student researcher in London, United Kingdom!
  • [2025.03]: I passed my Ph.D. thesis proposal review!
  • [2025.02]: I was invited to give a talk titled On the Interpretability and Safety of Generative Models by research week open house of NUS!
  • [2025.01]: Two papers with one spotlight and one poster got accepted to International Conference on Learning Representations (ICLR'2025), one paper got accepted to Transactions on Machine Learning Research (TMLR'2025)!
  • [2025.01]: I gave a poster presentation about Agent Smith during Global Young Scientists Summit 2025!
  • [2024.10]: I was selected as a participant for Global Young Scientists Summit 2025!
  • [2024.07]: I received Dean's Graduate Research Excellence Award from School of Computing, NUS!
  • [2024.05]: One paper got accepted to International Conference on Machine Learning (ICML'2024)!
  • [2024.02]: One paper got accepted to ACM Transactions on Multimedia Computing Communications and Applications (TOMM'2024)!
  • [2024.02]: We released Agent Smith, which got posted as "Here Come the AI Worms" on WIRED Magazine!

Selected Research
* denotes equal contribution, † denotes correspondence. Please see my CV or Google Scholar for full list. My representative papers are highlighted.
LLMs Pre-training and Attention
When Attention Sink Emerges in Language Models: An Empirical View
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
Why Do LLMs Attend to the First Token?
Federico Barbero*†, รlvaro Arroyo*, Xiangming Gu, Christos Perivolaropoulos, Michael Bronstein, Petar Veliฤkoviฤ‡, Razvan Pascanu
Conference on Language Modeling (COLM), Montreal, Canada, 2025.
pdf
SkyLadder: Better and Faster Pretraining via Context Window Scheduling
Tongyao Zhu, Qian Liu†, Haonan Wang, Shiqi Chen, Xiangming Gu, Tianyu Pang, Min-Yen Kan
Annual Conference on Neural Information Processing Systems (NeurIPS), San Diego, USA, 2025.
Also in International Conference on Learning Representations Workshop on Open Science for Foundation Models (SCI-FM @ ICLR), Singapore, Singapore, 2025.
pdf / code
Safety/Security of LLMs and Diffusion Models
Extracting Alignment Data in Open Models
Federico Barbero†, Xiangming Gu, Christopher A. Choquette-Choo, Chawin Sitawarin, Matthew Jagielski, Itay Yona, Petar Veliฤkoviฤ‡, Ilia Shumailov, Jamie Hayes
Technical Report, 2025.
pdf
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
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 / WIRED press
On Memorization in Diffusion Models
Xiangming Gu, Chao Du†, Tianyu Pang†, Chongxuan Li, Min Lin, Ye Wang
Transactions on Machine Learning Research (TMLR), 2025.
pdf / code
On Calibration of LLM-based Guard Models for Reliable Content Moderation
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/Singing and Multimodality
Automatic Lyric Transcription and Automatic Music Transcription from Multimodal Singing
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
Elucidating Gender Fairness in Singing Voice Transcription
Xiangming Gu, Wei Zeng, Ye Wang
ACM International Conference on Multimedia (MM), Ottawa, Canada, 2023.
pdf / code / video / poster
MM-ALT: A Multimodal Automatic Lyric Transcription System
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
Transfer Learning of wav2vec 2.0 for Automatic Lyric Transcription
Longshen Ou*, Xiangming Gu*, Ye Wang
International Society for Music Information Retrieval Conference (ISMIR), Bengaluru, India, 2022.
pdf / code

Honors and Awards
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, 2025/2022
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

Talks or Sharings
Google Deepmind Team DL: Agent Frontier, talk on Looking into LLMs: From Tokens to Solutions, 2025
Google Deepmind Team DL: Agent Frontier, talk on Understanding Attention Sink in (Large) Language Models, 2025
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

Academic Services
Conference reviewer for NeurIPS 2025/2024, ICML 2025, ICLR 2026/2025, CVPR 2026/2025, ICCV 2025/2023, ECCV 2024, ACL ARR 2025/2024, MM 2025/2024, IJCAI 2024, AISTATS 2026/2025/2021
Journal reviewer for TPAMI, TOMM, TASLP, RA-L

Teaching
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

Miscellaneous
I love tourism, movies, food, etc. I have been lived in ๐Ÿ‡จ๐Ÿ‡ณ๐Ÿ‡ธ๐Ÿ‡ฌ๐Ÿ‡ฌ๐Ÿ‡ง, and travelled to ๐Ÿ‡น๐Ÿ‡ญ๐Ÿ‡ซ๐Ÿ‡ฎ๐Ÿ‡ต๐Ÿ‡น๐Ÿ‡ง๐Ÿ‡ช๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ‡ญ๐Ÿ‡ฐ๐Ÿ‡ฒ๐Ÿ‡พ๐Ÿ‡จ๐Ÿ‡ฆ๐Ÿ‡ฆ๐Ÿ‡ช๐Ÿ‡ฆ๐Ÿ‡น๐Ÿ‡ฏ๐Ÿ‡ต๐Ÿ‡ญ๐Ÿ‡บ๐Ÿ‡จ๐Ÿ‡ฟ๐Ÿ‡ฎ๐Ÿ‡น๐Ÿ‡ป๐Ÿ‡ฆ๐Ÿ‡ญ๐Ÿ‡ท๐Ÿ‡ซ๐Ÿ‡ท๐Ÿ‡จ๐Ÿ‡ญ๐Ÿ‡ฉ๐Ÿ‡ช๐Ÿ‡ณ๐Ÿ‡ฑ for holidays/conferences.


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