me.jpeg

Hongfu Liu (刘洪甫)

Contact: liu (dot) hongfu [at] u (dot) nus (dot) edu

Hi! I am a third-year Ph.D. student in the Sound and Music Computing Lab at National University of Singapore. I am fortunate to be advised by Prof. Ye Wang. Previously, I obtained my Bachelor’s degree in Computer Science at Zhejiang University. I also spent a great semester in my senior year at UC Berkeley and visited CNMAT.

I am broadly interested in machine learning for NLP, Speech, and Music topics. Currently, I focus more on improving large language (foundation) models by: (1) designing data-efficient approaches; (2) understanding the safety and robustness; (3) evaluating large language model agents.

News

Oct, 2023 One paper got accepted to the Findings of EMNLP 2023!
May, 2023 One paper got accepted to Interspeech 2023!
Nov, 2022 One paper got accepted to Advances in Neural Information Processing Systems 2022!
May, 2022 I passed my Ph.D. Qualifying Examination (PQE) and became a Ph.D. candidate!
May, 2021 One paper got accepted to International Conference on Machine Learning 2021!

Publications

  1. arXiv
    Advancing Test-Time Adaptation for Acoustic Foundation Models in Open-World Shifts
    Hongfu Liu, Hengguan Huang, and Ye Wang
    In arXiv preprint 2023
    PDF
  2. EMNLP Findings
    Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning
    Hongfu Liu, and Ye Wang
    In Findings of the Conference on Empirical Methods in Natural Language Processing 2023
    PDF Code
  3. Interspeech
    Zero-Shot Automatic Pronunciation Assessment
    Hongfu Liu, Mingqian Shi, and Ye Wang
    In Interspeech 2023
    PDF
  4. NeurIPS
    Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation
    Hengguan Huang, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, and Ye Wang
    In Advances in Neural Information Processing Systems 2022
    PDF Code
  5. ICML
    STRODE: Stochastic Boundary Ordinary Differential Equation
    Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, and Ye Wang
    In International Conference on Machine Learning 2021
    PDF Code
  6. CSMC+ MuMe
    A Study on Neural Models for Target-Based Computer-Assisted Musical Orchestration
    Carmine Cella, Luke Dzwonczyk, Alejandro Saldarriaga-Fuertes, Hongfu Liu, and Helene-Camille Crayencour
    In 2020 Joint Conference on AI Music Creativity (CSMC+ MuMe) 2020
    PDF
  7. ACM MM
    Mind Band: a crossmedia AI music composing platform
    Zhaolin Qiu, Yufan Ren, Canchen Li, Hongfu Liu, Yifan Huang, Yiheng Yang, Songruoyao Wu, Hanjia Zheng, Juntao Ji, Jianjia Yu, and  others
    In Proceedings of the 27th ACM international conference on multimedia 2019
    PDF

Academic Reviewers

  • ICCV 2023

  • ICLR 2022, 2024


Teaching

  • CS4347: Sound and Music Computing (2022 Spring / 2022 Fall)

  • CS5242: Neural Networks and Deep Learning (2021 Fall / 2023 Spring)