SPaCe — Self-Paced Curriculum for LLMs
Self-paced curriculum learning that combines cluster-based data reduction with a multi-armed bandit sampler, matching baselines while using up to 100× fewer training samples.
ACL 2026
About
My name is Van Dai Do. I build efficient & safe LLMs—reinforcement learning, activation steering with memory, and retrieval-guided decoding. Additionally, I work on time-series forecasting, mostly with foundational models and edit-based methods. I am currently a Associate Research Fellow at Deakin University’s Applied AI Institute (A2I2).
News
🔊I was awarded "Gold Reviewer" for ICML 2026!
🎉1 paper accepted to ICML 2026
🎉1 paper accepted to ACL 2026
🔊 I am invited to present my ACL 2025 poster at Kingston AI Group Symposium 2026, held by Australian Institute for Machine Learning (AIML) at Adelaide!
📖 I submitted my PhD thesis titled “Efficient and Safe Large Language Models with Reinforcement Learning” after 2 years and 5 months on this journey! Very grateful for the support of my great supervisors Dr. Hung Le and Professor Svetha Venkatesh.
🎉1 paper accepted to TMLR with Journal to Conference (J2C) Certification!
🎉1 paper accepted to ICDM 2025
🎉 I won the 3-Minute Thesis (3MT) competition hosted by Deakin’s A2I2. What a great journey—grateful for the experience and everyone who supported me along the way.
🎉1 paper accepted to EMNLP 2025
🎉1 paper accepted to ACL 2025
📖I started working as a Research Assistant under Dr. Hung Le's supervision on the Australian Research Council (ARC) DECRA grant to implement innovative time series forecasting models.
🎉1 paper accepted to ECAI 2024
📖Invited tutorial at AAMAS
🛫I started my PhD journey at Applied Artificial Intelligence Initiative (A2I2), Deakin University, Australia with a full-ride HDR scholarship!
Projects
Reviving Error Correction in Time-Series Forecasting
An architecture-agnostic error-correction module that plugs into any forecaster without retraining; decomposes corrections into trend and seasonal components for robust gains across models and datasets.
ICML 2026
Reasoning Under 1 Billion
Guiding Reinforcement Fine-tuning with Intrinsic External Episodic Memory reward.
TMLR 2025
ALEC — Alignment Learning with Episodic Control
Non-parametric inference-time alignment with episodic memory; sample-efficient alignment under sparse feedback.
EMNLP 2025
DSEM — Dynamic Steering with Episodic Memory
Training-free token-level activation steering using episodic memory; adaptive alignment across safety & style.
ACL 2025
Prompting with Episodic Memory
RL-based prompt example selection from episodic memory to boost generalization across NLP tasks.
ECAI 2024 (Oral)
Publications
SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
ACL 2026
Van Dai Do, Manh Nguyen, Svetha Venkatesh, Hung Le — PDF
Van Dai Do, Manh Nguyen, Svetha Venkatesh, Hung Le — PDF
Reviving Error Correction in Modern Deep Time-Series Forecasting
ICML 2026
Minh Hoang Nguyen, Van Dai Do, Huu Hiep Nguyen, Dung Nguyen, Kien Do, Hung Le — OpenReview
Minh Hoang Nguyen, Van Dai Do, Huu Hiep Nguyen, Dung Nguyen, Kien Do, Hung Le — OpenReview
Sample Efficient Alignment Learning With Episodic Control
EMNLP 2025
Van Dai Do, Quan Tran, Ahmed Kirmani, Lu Zhang, Hung Le
Van Dai Do, Quan Tran, Ahmed Kirmani, Lu Zhang, Hung Le
Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
TMLR 2025
Hung Le, Van Dai Do, Dung Nguyen, Svetha Venkatesh
Hung Le, Van Dai Do, Dung Nguyen, Svetha Venkatesh
Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
ICDM 2025
Hung Le, Sherif Abbas, Minh Hoang Nguyen, Van Dai Do, Huu Hiep Nguyen, Dung Nguyen
Hung Le, Sherif Abbas, Minh Hoang Nguyen, Van Dai Do, Huu Hiep Nguyen, Dung Nguyen
Large Language Models Prompting With Episodic Memory
ECAI 2024 (Oral)
Van Dai Do, Quan Tran, Svetha Venkatesh, Hung Le — Code
Van Dai Do, Quan Tran, Svetha Venkatesh, Hung Le — Code
Deep RL for Multi-Hop Offloading in UAV-Assisted Edge Computing
IEEE TVT 2023
Nguyen Tien Hoa, Van Dai Do, Le Hoang Lan, Nguyen Cong Luong, Duc Van Le, Dusit Niyato — Link
Nguyen Tien Hoa, Van Dai Do, Le Hoang Lan, Nguyen Cong Luong, Duc Van Le, Dusit Niyato — Link
Professional Service
Reviewer — Neurips 2026
Reviewer — ICML 2026 Gold Reviewer
Reviewer — ACL Rolling Review (ARR)
Contact
Email: [email protected] · Phone: +61 412 242 886
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