Retrieval-Augmented Forecasting

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2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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RAEGL: Risk-Aware Evidence-Gated Learning for Selective Contextual Routing under Temporal Shift
Sep 27, 2026Yifan GuoConformal Risk Control Retrieval-Augmented Forecasting
Stony Brook University
SGA: Uncertainty Quantification for Multi-Step Forecasting in Time Series Foundation Models
Sep 23, 2026Xin-Yu Hu, Shuang Liang, Cheng Feng +1Retrieval-Augmented Forecasting Time Series Foundation Models
National Key Laboratory for Novel Software Technology, Nanjing University, China. · School of Intelligent Science and Technology, Nanjing University, China. · Siemens Data and AI Research, Beijing, China. +1
A Two-Stage Forecasting System for CPU Workload Prediction in Private Clouds
Sep 3, 2026Ashir Javeed, Anton Borg, Håkan Grahn +3Retrieval-Augmented Forecasting Cloud
Department of Computer Science, Blekinge Institute of Technology, 371 79, Sweden · Ericsson AB, 371 33 Karlskrona, Sweden
FarSky: Task-Aware Latent-Space Coupling for Generative Intra-Hour Solar Forecasting
Aug 6, 2026Yann Fabel, Bijan Nouri, Milon Miah +4Energy Forecasting Retrieval-Augmented Forecasting
1DLR, Institute of Solar Research · 2RWTH Aachen University · 3CIEMAT, Energy Department, Renewable Energy Division
Align-RAG: Alignment Is All You Need for TSFM In-Context Learning
Aug 6, 2026Mohammad Asadi, Soheil Hor, Bardiya Akhbari +6Retrieval-Augmented Forecasting Time Series Foundation Models
1Stanford University 2Amazon
Spatiotemporal Graph Transformer for Traffic Intelligence in Edge Computing
Aug 4, 2026Laha Ale, Letian Lin, Na Cao +2Accurate Traffic Forecasting Temporal Graph Neural Networks
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China · SWJTU-Leeds Joint School, Southwest Jiaotong University, Chengdu, China · Key Lab of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China +1
Traceable Multi-Agent System for Knowledge-Based Forecasting
Aug 4, 2026Junhyeok Kang, Sangjun Han, Hyeokjun Choe +1Retrieval-Augmented Forecasting Forecast
LG AI Research · Seoul, Republic of Korea
CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting
Aug 4, 2026Xiaoyu Tao, Mingyue Cheng, Bokai Pan +6Retrieval-Augmented Forecasting Contextual Reasoning
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China, Hefei, Anhui Province, China
TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion
Jul 31, 2026Yu Sun, Yuan Chang, Xiaohou Shi +1Multivariate Time Series Forecasting Retrieval-Augmented Forecasting
Beijing University of Posts and Telecommunications Beijing, China · China Telecom Research Institute Beijing, China
From Seasonality to Semantics: Benchmarking a Hybrid Probabilistic Forecasting System for Roadblocks in Bolivia
Jul 23, 2026Rodrigo Vargas Sainz, Christian Berón CurtiRetrieval-Augmented Forecasting Season
Universidad Privada de Santa Cruz de la Sierra
NaviAIS: A Scenario-Level Vessel Trajectory Prediction Dataset withVectorized Lane Priors and the NaviLane Forecasting Framework
Jul 21, 2026Yuan Gui, Hongchen Luo, Liqi Qu +2Maritime Navigation Automatic Identification System
Northeastern University, Shenyang 110819, China
Self-Gating Attention for Efficient Time Series Forecasting
Jul 2, 2026Dezheng Wang, Tong Chen, Wei Yuan +3Temporal Attention Time Series Forecasting
School of Automation, Southeast University, 210096, China · School of Electrical Engineering and Computer Science, The University of Queensland, QLD 4072, Australia
StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting
Jun 30, 2026Haroon Gharwi, Yue Dai, Kai ShuRetrieval-Augmented Forecasting Time Series Forecasting
Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA · Department of Computer Science, Emory University, Atlanta, GA, USA
ForecastAgentSearch: Towards a Multi-Expert Agent Search System for Geopolitical Event Forecasting
Jun 30, 2026Miaomiao Cai, He Chang, Yunshan Ma +1Retrieval-Augmented Forecasting Forecast
National University of Singapore Singapore, Singapore · Communication University of China Beijing, China · Singapore Management University Singapore, Singapore
FDN: Interpretable Spatiotemporal Forecasting with Future Decomposition Networks
Jun 23, 2026Nicholas Majeske, Ariful AzadSpatio-Temporal Forecasting Retrieval-Augmented Forecasting
Department of Intelligent Systems Engineering, Indiana University Bloomington, USA · Department of Computer Science and Engineering, Texas A&M University, USA
Simulation-Augmented Multi-Step Split Conformal Prediction for Aggregated Forecasts
Jun 15, 2026Andro SabashviliOnline Conformal Prediction Retrieval-Augmented Forecasting
Once-for-All: Scalable Simultaneous Forecasting via Equilibrium State Estimation
Jun 11, 2026Beinan Xu, Andy Song, Jiti Gao +1Retrieval-Augmented Forecasting Data-Driven Forecasting
School of Computing Technologies, RMIT University, Melbourne, Australia · Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia · School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
Reconstructing and forecasting disease trajectories of patients with Alzheimer's disease using routine data in resource-constrained settings
Jun 5, 2026Ratnadeep Das, Atri Chatterjee, Sitikantha RoyAlzheimer Readmission Prediction
Yardi School of Artificial Intelligence (ScAI), Indian Institute of Technology Delhi, Hauz Khas, Delhi, 110016, India · Department of Neurology, Vardhman Mahavir Medical College and Safdarjung Hospital, Delhi, 110029, India · Department of Applied Mechanics, Indian Institute of Technology Delhi, Hauz Khas, Delhi, 110016, India
Bridging the Last Mile of Time Series Forecasting with LLM Agents
Jun 1, 2026Yuhua Liao, Zetian Wang, Qiangqiang Nie +1Retrieval-Augmented Forecasting Time Series Forecasting
Trip.com Group, Shanghai, China
Hybrid Probabilistic Forecasting of Under-Five Malaria Admissions in Ghana: A Gaussian Process Regression with Holt-Winters Smoothing
May 30, 2026T. Ansah-Narh, Y. Asare Afrane, J. Bremang TandohAccurate Dengue Forecasting Retrieval-Augmented Forecasting
ForecastCompass: Guiding Agentic Forecasting with Adaptive Factor Memory
May 29, 2026Yurui Chang, Yongkang Du, Yuanpu Cao +2Retrieval-Augmented Forecasting Semantic Memory
Pennsylvania State University
KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning
May 28, 2026Kun Feng, Ziwei Shan, Yuchen Fang +6Retrieval-Augmented Forecasting Time Series Forecasting
ShanghaiTech University · Ant Group
Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations
May 25, 2026Eduardo Luiz Alba, Gilson Adamczuk Oliveira, Matheus Henrique Dal Molin Ribeiro +1Electricity Price Forecasting Shapley Additive Explanations
Industrial & Systems Engineering Graduate Program (PPGEPS), Federal University of Technology-Parana (UTFPR), Via do Conhecimento, KM 0l—Fraron, Pato Branco 85503-390, PR, Brazil
SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction
May 18, 2026Gustav Olaf Yunus Laitinen-Fredriksson Lundström-Imanov, Hafize Gonca CömertRetrieval-Augmented Forecasting Online Conformal Prediction
Department of Economics, Stockholm University, SE-106 91 Stockholm, Sweden
Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting
May 16, 2026Qian Jiang, Liping SunRetrieval-Augmented Forecasting Next-State Prediction
School of Computing · The Australian National University · Canberra, ACT 2601, Australia +3
Nexus : An Agentic Framework for Time Series Forecasting
May 14, 2026Sarkar Snigdha Sarathi Das, Palash Goyal, Mihir Parmar +6Retrieval-Augmented Forecasting Time Series Foundation Models
1Google · 2Pennsylvania State University
Unlocking air traffic flow prediction through microscopic aircraft-state modeling
May 11, 2026Bin Wang, Anqi Liu, Jiangtao Zhao +8Accurate Traffic Forecasting Air Traffic Control
Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, Shandong, China. · Sanya Oceanographic Institution, Ocean University of China, Sanya, 572022, Hainan, China. · Joint Laboratory of Data Science and Business Intelligence, Southwestern University of Finance and Economics, Chengdu, 610000, Sichuan, China. +2
LEAF: A Living Benchmark for Event-Augmented Forecasting
May 9, 2026Mingtian Tan, Mihir Parmar, Palash Goyal +5Large Language Model Forecasting Retrieval-Augmented Forecasting
Google · University of Virginia
Reasoning-Aware Training for Time Series Forecasting
May 9, 2026Md Atik Ahamed, Mihir Parmar, Palash Goyal +4Time Series Foundation Models Retrieval-Augmented Forecasting
1Google · University of Kentucky
Retrieval Mechanisms Surpass Long-Context Scaling in Time Series Forecasting
May 6, 2026Rishi Ahuja, Kumar Prateek, Simranjit Singh +1Time Series Foundation Models Retrieval-Augmented Forecasting
Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, 144008, India.
CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting
Apr 30, 2026Bokai Pan, Mingyue Cheng, Zhiding Liu +6Retrieval-Augmented Forecasting Time Series Forecasting
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China, Hefei 230026, China
Prior-Agnostic Robust Forecast Aggregation
Apr 27, 2026Zhi Chen, Cheng Peng, Wei TangRetrieval-Augmented Forecasting Logistic Regression
Chinese University of Hong Kong
Channel-wise Retrieval for Multivariate Time Series Forecasting
Apr 7, 2026Junhyeok Kang, Jun Seo, Soyeon Park +4Multivariate Time Series Forecasting Retrieval-Augmented Forecasting
LG AI Research, Republic of Korea
Overcoming the Modality Gap in Context-Aided Forecasting
Mar 12, 2026Vincent Zhihao Zheng, Étienne Marcotte, Arjun Ashok +4Retrieval-Augmented Forecasting Data Augmentation
ServiceNow AI Research, Montréal, Canada · Department of Civil Engineering, McGill University, Montréal, Canada · DIRO, Université de Montréal, Montréal, Canada +1
Adaptive Automatic Model Selection for Demand Forecasting under Heterogeneous Demand Patterns
Feb 15, 2026Adolfo González, Víctor ParadaModel Selection Retrieval-Augmented Forecasting
Department of Computer Engineering and Informatics, Faculty of Engineering, University of Santiago of Chile, Santiago, Chile
Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting
Jan 23, 2026Haonan Yang, Jianchao Tang, Zhuo LiRetrieval-Augmented Forecasting Time Series
National University of Defense Technology, Changsha, Hunan, China
GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting
Jan 8, 2026Shovito Barua Soumma, Hassan GhasemzadehContinuous Glucose Monitoring Diabetes
College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA · School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA

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RAEGL: Risk-Aware Evidence-Gated Learning for Selective Contextual Routing under Temporal Shift

Yifan Guo

Stony Brook University

Conformal Risk Control Retrieval-Augmented Forecasting

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Contextual specialization can improve forecasting accuracy, but a correction selected on one historical interval may become unreliable under temporal distribution shift. To address this issue, we propose RAEGL, a Risk-Aware Evidence-Gated Learning framework for selective contextual forecasting. RAEGL retains a validated global predictor by default and activates a contextual residual only when pre-deployment evidence supports its use. The framework separates candidate selection from gate calibration and jointly evaluates randomization significance, practically meaningful gain, and temporal stability. Experiments on real-world audits and controlled panels show how RAEGL can prevent harmful contextual deployment while making conservative opportunity costs explicit. In a reconstructed Our World in Data audit, exact fallback avoids RMSE degradations of 0.0960 and 0.0239 caused by two validation-selected corrections. In a sealed World Development Indicators evaluation, a region-based correction passes the randomization test but is withheld because its gain is only 0.000092, its country-clustered 95% confidence interval crosses zero, and only 0.02% of bootstrap replicates reach the practical threshold. In controlled panels, the stability- and support-aware extension activates in 97.2% of strong, stable-context runs while rejecting all high-drift settings. These results support RAEGL as an auditable, evidence-based mechanism for managing contextual deployment risk and as a conservative alternative to validation-driven contextual selection.

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