15 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…
Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
Zhao Tan, Yiji Zhao, Shiyu Wang +5
Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries from massive temporal records. H…
Learning from Complexity: Exploring Dynamic Sample Pruning of Spatio-Temporal Training
Wei Chen, Junle Chen, Yuqian Wu +2
Spatio-temporal forecasting is fundamental to intelligent systems in transportation, climate science, and urban planning. However, training deep learning models on the massive, oft…
Select, then Balance: Exploring Exogenous Variable Modeling of Spatio-Temporal Forecasting
Wei Chen, Yuqian Wu, Yuanshao Zhu +4
Spatio-temporal (ST) forecasting is critical for dynamic systems, yet existing methods predominantly rely on modeling a limited set of observed target variables. In this paper, we…
Test-Time Learning of Causal Structure from Interventional Data
Wei Chen, Rui Ding, Bojun Huang +5
Supervised causal learning has shown promise in causal discovery, yet it often struggles with generalization across diverse interventional settings, particularly when intervention…
Hierarchical Reinforcement Learning for Cooperative Air-Ground Delivery in Urban System
Songxin Lei, Chunming Ma, Haomin Wen +7
Cooperative air-ground delivery has emerged as a promising logistics paradigm by leveraging the complementary strengths of UAVs and ground carriers. However, effective dispatching…