Low-Rank Adaptation for Foundation Models: A Comprehensive Review
The rapid advancement of foundation modelslarge-scale neural networks trained on
diverse, extensive datasetshas revolutionized artificial intelligence, enabling unprecedented …
diverse, extensive datasetshas revolutionized artificial intelligence, enabling unprecedented …
Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting
Predicting spatio-temporal traffic flow presents significant challenges due to complex
interactions between spatial and temporal factors. Existing approaches often address these …
interactions between spatial and temporal factors. Existing approaches often address these …
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
The widespread deployment of sensing devices leads to a surge in data for spatio-temporal
forecasting applications such as traffic flow, air quality, and wind energy. Although spatio …
forecasting applications such as traffic flow, air quality, and wind energy. Although spatio …
Spatiotemporal Backward Inconsistency Learning Gives STGNNs Icing on the Cake
Spatiotemporal prediction models facilitate various smart-city applications across various
domains, such as traffic and climate. While current advancements in these models …
domains, such as traffic and climate. While current advancements in these models …