Nhat M. Hoang

Nhat M. Hoang

CS Undergraduate Student

Nanyang Technological University

Hello There!

My name is Nhat Minh Hoang, an enthusiastic Computer Science undergraduate at Nanyang Technological University (NTU), Singapore. I’m thrilled to be a part of NTU Nail Lab, where I’m working under the guidance of Prof. Luu Anh Tuan.

My research interests lie in the realm of Natural Language Processing (NLP), I’m particularly captivated by generative models, multimodal models, and how they align with human purposes, such as educational applications and sentiment analysis.

Interests
  • Generative AI
  • Large Language Models
  • Multimodal Learning
Education
  • BE in Computer Science, 2020 - 2024

    Nanyang Technological University

Recent News

  • [Mar. 2024] 1 paper (co-first) accepted at NAACL 2024. πŸŽ‰

  • [Dec. 2023] 1 paper (1st author) accepted at AAAI 2024. πŸŽ‰

  • [Nov. 2023] 1 paper (co-first) accepted at ACM SAC 2024. πŸŽ‰

  • [Jul. 2023] 1 paper (2nd author) accepted at ICIP 2023. πŸŽ‰

Publications

(2024). ToXCL: A Unified Framework for Toxic Speech Detection and Explanation. NAACL 2024.

PDF Cite Code

(2024). MotionMix: Weakly-Supervised Diffusion for Controllable Motion Generation. AAAI 2024.

PDF Cite Code Project Page

(2023). ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math Question. ACM/SIGAPP SAC 2024.

PDF Cite Code

(2023). Data Augmentation Using Corner CutMix and an Auxiliary Self-Supervised Loss. ICIP 2023.

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Experience

 
 
 
 
 
Huawei Singapore Research Centre
Algorithm Engineer Intern
March 2023 – November 2023 Singapore
  • Worked on “Diffusion Model for Controllable Human Motion Generation” and “3D Multimodal LLM” projects.
  • Recipient of “Outstanding Intern Award 2023”, representative to go on stage.
  • Advisor: Dr. Kehong Gong
 
 
 
 
 
NTU AI Language Lab (NAIL Lab)
Undergraduate Research Assistant
October 2021 – Present Singapore
  • Currently working on the application of Diffusion Model in NLP.
  • Worked on “Hate Speech Detection & Explanation” and “LLMs & Math Word Problems” projects.
  • Advisor: Prof. Luu Anh Tuan
 
 
 
 
 
Institute for Infocomm Research (I2R), A*STAR
Computer Vision Research Intern
June 2022 – December 2022 Singapore
  • Designed an novel data augmentation approach with an auxiliary supervised loss to enhance generalization performance in self-supervised and transfer learning settings.
  • Paper published at ICIP 2023.
  • Advisors: Dr. Qianli Xu and Dr. Fen Fang
 
 
 
 
 
Eureka Robotics
Computer Vision Engineer Intern
January 2022 – April 2022 Singapore
  • Worked on building a stereo-matching model on AWS.
  • Overcame limited availability of data by synthesized 1,000+ images using Blender.
  • Advisor: Dr. Hung Pham
 
 
 
 
 
Ubisoft Singapore
Data Scientist Intern
July 2021 – October 2021 Singapore
  • Collaborated to optimize a recomendation system by analyzing large-scale datasets and re-implementing sota models.
  • Advisors: Julien Bluteau and Dr. Chedy RaΓ―ssi