arXiv:2601. 13591v2 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning.
By Maojun Sun, Yifei Xie, Yue Wu, Ruijian Han, Binyan Jiang, Defeng Sun, Yancheng Yuan, Jian Huang
arXiv:2606. 28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost.
By Anisha Pal, Aodhan Sweeney, Kyle Heyblom, Kalai Ramea
arXiv:2606. 11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify because multi-sensor observations are rarely available in consistent, analysis-ready form at the necessary spatiotemporal scales.
By Jonathan Starfeldt, Maria J. Molina, Alexander Kerr, Adam Yang, Thomas R. H. Holmes, Christopher R. Hain
arXiv:2509. 13805v4 Announce Type: replace-cross Abstract: Foundation models have revolutionized natural language processing through a ``train once, deploy anywhere'' paradigm, where a single pre-trained model adapts to countless downstream tasks without retraining.
By Florian Wiesner, Zo\"e J. Gray, Matthias Wessling, Stephen Baek
arXiv:2606. 02852v1 Announce Type: new Abstract: Accurate short-term forecasting of residential energy load and indoor temperature is essential for home energy management systems, grid-level demand response, and community energy efficiency efforts.
By Jainam Dhruva, Yousaf Raza, A. B. Siddique, Simone Silvestri
arXiv:2607. 03585v1 Announce Type: new Abstract: Engineering Digital Twins and Prognostics and Health Management (PHM) systems rely on robust perception modules to extract actionable information from heterogeneous and non-stationary time-series data.
By Quang Hung Pham, Ryad Zemouri, Martin Gagnon, Luc Vouligny