Time series forecasting is essential for operational intelligence in the hospitality industry, and particularly challenging in large-scale, distributed systems. This study evaluates the performance of statistical, machine learning (ML), deep learning, and foundation models in forecasting hourly sales over a 14-day horizon using real-world data from a network of thousands of restaurants across Germany. The forecasting solution includes features such as weather conditions, calendar events, and time-of-day patterns. Results demonstrate the strong performance of ML-based meta-models and highlight the emerging potential of foundation models like Chronos and TimesFM, which deliver competitive performance with minimal feature engineering, leveraging only the pre-trained model (zero-shot inference). Additionally, a hybrid PySpark-Pandas approach proves to be a robust solution for achieving horizontal scalability in large-scale deployments.
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
University of Science and Technology of China（中国科学技术大学）；Computer Network Information Center, Chinese Academy of Sciences（中国科学院计算机网络信息中心）；Baidu Inc.（百度公司）；Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能研究院）；AI Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）AI 分支）
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
Institute of Computing Technology, CAS（中国科学院计算技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）；School of Computer Science and Technology, Huazhong University of Science and Technology（华中科技大学计算机科学与技术学院）；Tsinghua University（清华大学）；School of Computer Science and Engineering, The University of New South Wales（新南威尔士大学计算机科学与工程学院）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）；Department of Computer Science, Aalborg University（奥尔堡大学计算机科学系）
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
Morgan Stanley（摩根士丹利）；ServiceNow Research（ServiceNow 研究院）；Université de Montréal（蒙特利尔大学）；Mila-Quebec AI Institute（米拉-魁北克人工智能研究所）；McGill University（麦吉尔大学）
QKCV Attention: Enhancing Time Series Forecasting with Static Categorical Embeddings for Both Lightweight and Pre-trained Foundation Models
Independent Researcher（独立研究者）；Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai)（信息行为脑机智能关键实验室）；School of Business and Management（商学院）
RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges
The Hong Kong University of Science and Technology（香港科学与技术大学）；Nanjing University（南京大学）；Southern University of Science and Technology（南方科技大学）；Shanghai AI Laboratory（上海人工智能实验室）；Shanghai TechWind Technology Co., Ltd.（上海技风科技有限公司）
Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning
University of New South Wales（新南威尔士大学）；CSIRO（联邦科学与工业研究组织）
Distilling Time Series Foundation Models for Efficient Forecasting
The City College of New York, City University of New York, USA（纽约城市学院，纽约城市大学）；Institute of Computing Technology, Chinese Academy of Sciences, China（中国科学院计算技术研究所）；Stevens Institute of Technology, USA（史蒂文斯理工学院）
Benchmarking Probabilistic Time Series Forecasting Models on Neural Activity
Department of Applied Mathematics, University of Washington（应用数学系，华盛顿大学）；Department of Neurobiology and Biophysics, University of Washington（神经生物学与生物物理学系，华盛顿大学）；Allen Institute for Brain Science（脑科学研究所）；Department of Electrical and Computer Engineering, University of Washington（电气与计算机工程系，华盛顿大学）
Simple and Robust Forecasting of Spatiotemporally Correlated Small Earth Data with A Tabular Foundation Model
School of Engineering and Technology, China University of Geosciences (Beijing)（工程与技术学院，中国地质大学（北京））；School of Geological Engineering and Geomatics, Chang'an University（地质工程与测绘学院，长安大学）
How Foundational are Foundation Models for Time Series Forecasting?
Univ. Rennes（里昂大学）；CNRS（法国国家科学研究中心）；Inria（法国国家信息与自动化技术研究所）；IRISA - UMR 6074（国际信息与自动化研究所）；Univ. Grenoble Alpes（格勒诺布尔阿尔卑斯大学）；Univ. Savoie Mont Blanc（萨瓦伊-蒙布莱大学）；LPNC（实验室）；CEA（法国原子能委员会）；LIST（法国国家信息与自动化技术研究所）
TimeFound: A Foundation Model for Time Series Forecasting
Baidu Research（百度研究院）；University of Science and Technology of China（中国科学技术大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
OpenECG: Benchmarking ECG Foundation Models with Public 1.2 Million Records
The First Affiliated Hospital, Jiangxi Medical College, Nanchang University（南昌大学江西医学院第一附属医院）；Nanchang University（南昌大学）；Georgia Institution of Technology（佐治亚理工学院）
