5 papers · 1 filter
SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting
Van Dai Do, Huu Hiep Nguyen, Minh Hoang Nguyen +1
Time series forecasting aims to predict future values from historical observations and auxiliary features. We propose \textbf{SteerCast}, a retrieval-based latent steering method t…
Lotus: Learning to Understand Time-series by Learning to Forecast
Van Dai Do, Huu Hiep Nguyen, Minh Hoang Nguyen +2
Time-series language models typically align numerical signals with language using labels, captions, or question-answer pairs. Although such supervision encourages linguistic repres…
Volatility-Clustering Adaptation for Financial Time Series
Manh Nguyen, Minh Hoang Nguyen, Huu Hiep Nguyen +2
Time-series foundation models are increasingly adapted to new domains through fine-tuning on target data, under the implicit assumption that more target data yields better forecast…
Memory in Deep Time-Series Models
Minh Hoang Nguyen, Huu Hiep Nguyen, Manh Nguyen +3
Deep learning for time series has progressed through successive architectural paradigms, from recurrent networks and transformers to structured state-space models, retrieval-augmen…
Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
Hung Le, Sherif Abbas, Minh Hoang Nguyen +3
Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) meth…