6 papers
TS-Memory: Plug-and-Play Memory for Time Series Foundation Models
Sisuo Lyu, Siru Zhong, Tiegang Chen +6
Time Series Foundation Models (TSFMs) achieve strong zero-shot forecasting through large-scale pre-training, but adapting them to downstream domains under distribution shift remain…
Think Before You Act: Intention-Guided Reasoning for LLM-Based Location Prediction
Qingxiang Liu, Anqi Liang, Zhuoyang Jiang +5
Predicting a user's next Point-of-Interest (POI) based on their historical check-in records is a fundamental task in location-based services. While recent methods incorporating lar…
RAST: A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
Weilin Ruan, Xilin Dang, Ziyu Zhou +2
Traffic prediction is a cornerstone of modern intelligent transportation systems and a critical task in spatio-temporal forecasting. Although advanced Spatio-temporal Graph Neural…
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
Sisuo Lyu, Siru Zhong, Weilin Ruan +4
Time series forecasting is fundamental to diverse applications, with recent approaches leverage large vision models (LVMs) to capture temporal patterns through visual representatio…
Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey
Wei Dai, Shengen Wu, Wei Wu +7
Trajectory prediction serves as a critical functionality in autonomous driving, enabling the anticipation of future motion paths for traffic participants such as vehicles and pedes…
Multi-view Hypergraph-based Contrastive Learning Model for Cold-Start Micro-video Recommendation
Sisuo Lyu, Xiuze Zhou, Xuming Hu
With the widespread use of mobile devices and the rapid growth of micro-video platforms such as TikTok and Kwai, the demand for personalized micro-video recommendation systems has…