4 papers
ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters
Yihang Lu, Xianwei Meng, Enhong Chen
Neural Forecasters (NFs) have become a cornerstone of Long-term Time Series Forecasting (LTSF). However, recent progress has been hampered by an overemphasis on architectural compl…
MNT-TNN: Spatiotemporal Traffic Data Imputation via Compact Multimode Nonlinear Transform-based Tensor Nuclear Norm
Yihang Lu, Mahwish Yousaf, Xianwei Meng +1
Imputation of random or non-random missing data is a long-standing research topic and a crucial application for Intelligent Transportation Systems (ITS). However, with the advent o…
Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation
Qitao Qin, Yucong Luo, Yihang Lu +3
Retrieval-Augmented Generation (RAG), by integrating non-parametric knowledge from external knowledge bases into models, has emerged as a promising approach to enhancing response a…
TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive Representations
Yihang Lu, Yangyang Xu, Qitao Qing +1
Recent deep learning models for Long-term Time Series Forecasting (LTSF) often emphasize complex, handcrafted designs, while simpler architectures like linear models or MLPs have o…