Ocean wave forecasting is essential for maritime safety, offshore operations, and coastal resilience, yet remains challenging due to systematic biases in physics-based models. Physical models, while widely used, rely on approximations and parameterizations that limit their accuracy under complex ocean-atmosphere condit...
Si-Yu Gan, Dong-Sheng Luo, K. Yuan et al.· 0 citations
A unified objective function for explainable time series learning that bridges attribution and counterfactual reasoning within a single framework is proposed and a novel explanation framework is introduced that learns a parametric transformation network to construct explanation-embedded instances.
Xu Zheng, Zichuan Liu, Zhuo-Min Chen et al.· 0 citations
IB-Forecast is proposed, an inherently interpretable multivariate time-series forecasting framework that decomposes forecasting into a learned periodic component and a residual component computed with explainable masks over input tokens that guarantees high explanation fidelity.
This work proposes MetaCaster, a meta-harness-optimized multi-agent framework that uses agentic data generation to automatically train specialized lightweight forecasters from only a few examples and textual contexts and highlights a new TSF paradigm in which agents act not as forecasters but as intermediary engineers...
Chengao Shen, Wen-Chao Yu, Fang-Yu Wu et al.· 0 citations
Compound flooding in managed coastal systems is influenced by hydrological conditions and water-management activity observed across multiple monitoring stations. Current forecasting models can capture temporal dependencies with low average errors, but global error metrics may conceal poor reproduction of prolonged high...
Liangjun You, Min Wu, Orlando Woods et al.· 0 citations
This work proposes Trajectory Graph Copilot, a novel framework that acts as a ``copilot'' for LLM agents by diagnosing potential action errors before they are executed, significantly enhancing the agent's ability to complete long-horizon tasks successfully.
Xu Zheng, Zhuomin Chen, Chaohao Lin et al.· arXiv.org· 0 citations
A novel framework, \textit{GAMER}~(Graph-based Action-centric Memory with Episodic Reasoning), that bridges the gap between inference scaling and episodic memory by decoupling the memory mechanism from LLMs.
