5 papers · 1 filter
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…
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…
Beluga Whale Detection from Satellite Imagery with Point Labels
Yijie Zheng, Jinxuan Yang, Yu Chen +3
Very high-resolution (VHR) satellite imagery has emerged as a powerful tool for monitoring marine animals on a large scale. However, existing deep learning-based whale detection me…
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…
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…