Jie Fu (付杰) is a happy and funny visiting scholar at Hong Kong University of Science and Technology (HKUST), chasing his human-friendly big AI dream.

He was a postdoctoral fellow (funded by Microsoft Research Montreal) supervised by Yoshua Bengio at University of Montreal, Quebec AI Institute (Mila). He was an IVADO postdoctoral fellow supervised by Chris Pal at Polytechnique Montreal, Quebec AI Institute (Mila). He worked as a researcher (PI) at BAAI (智源人工智能研究院). He obtained his PhD from National University of Singapore under the supervision of Tat-Seng Chua. He received outstanding paper awards at NAACL 2024, ICLR 2021.

His research agenda is centered around establishing an LLM within a unified, safe, and scalable world model framework, having an tight integration of System-1 (e.g., intuitive, fast) and System-2 (e.g., slow, logical, algorithmic, reasoning, planning) functionalities. More concretely:

  • Safe and Scalable System-2 Language Models: Human-AI Alignment, Reinforcement learning, Meta learning, Reasoning, Modular neural architectures, etc
  • Applications: Multi-modal learning (e.g., NLP, CV), Multi-modal embodied intelligence, AI for science, etc

Selected Publications

I’m (still…) training myself (slowly…)

My full publications can be found in Google Scholar.
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training
Tracking single cell evolution via clock-like chromatin accessibility
Nature Biotechnology 2024
HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts
ACL 2024
Think Before You Act: Decision Transformers with Working Memory
ICML 2024
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
ICLR 2024
TACO: Topics in Algorithmic COde generation dataset
AI Alignment: A Comprehensive Survey
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability
NeurIPS 2023
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
NeurIPS 2023, Datasets and Benchmarks Track
Running Ahead of Evolution - AI based Simulation for Predicting Future High-risk SARS-CoV-2 Variants
IJHPCA, ACM Gordon Bell COVID Finalist 2022
Interactive Natural Language Processing
MUDiff: Unified Diffusion for Complete Molecule Generation
LoG 2023
Learning Multi-Objective Curricula for Robotic Policy Learning
CoRL 2022
Biological Sequence Design with GFlowNets
ICML 2022