Retrieval-Augmented Time Series Forecasting

Ask about this topic

Overview

Retrieval-augmented time series forecasting studies how past examples, external information, or stored model errors can complement forecasts learned from numerical sequences. Common approaches retrieve similar historical windows or input-output analogs, then use alignment, cross-attention, gating, or weighted aggregation to combine them with a forecast; some methods use spectral or channel-wise matching, text and metadata, or residual-based correction. These methods are evaluated on settings such as long-horizon and zero-shot forecasting, non-stationary data, and cold-start or cross-region prediction, often alongside time-series foundation models. A central tension is that retrieved context can help with regime changes or limited observations but can also mislead when examples are poorly matched, stale, or selected using information unavailable at decision time.

Latest papers

CardsList

50 papers11 papers in the last four weeks, up 175% on the four weeks before. 0.1% of all new papers.

  1. RAG-CSI: Global Local Retrieval via Joint State and Dynamics Matching for CSI Prediction

    Oct 27, 2026Xinyue Jiang, Tong Li, Shiceng Zhang +2Channel State PredictionWireless Communications

    College of Computer Science and Electronic Engineering, Hunan University, Changsha, China. · Xidian University, Xian, China. · Peng Cheng Laboratory, Shenzhen 518066, China.

  2. When to Trust Memory: Retrieval-Guided Probabilistic Spatiotemporal Forecasting under Distribution Shift

    Oct 23, 2026Haochen Lv, Jianhao Zhang, Zhichen Lei +5Spatiotemporal ForecastingProbabilistic Forecasting

    School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China. · Key Laboratory of Big Data and Artificial Intelligence in Transportation, Ministry of Education, Beijing, China. · Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence, Beijing, China.

  3. A Model-Agnostic Correction Framework for Short-Term Building Load Forecasting

    Oct 22, 2026Shiqiao Zhou, Huanbo Lyu, Holger Schöner +5Electricity Load ForecastingTime Series Forecasting

    School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, West Midlands, United Kingdom · Siemens AG, Munich, 80333, Bavaria, Germany · School of Mathematics, University of Birmingham, Edgbaston, Birmingham, B15 2TT, West Midlands, United Kingdom +1

  4. ECHO: Correcting Time Series Foundation Model Forecasts with Historical Analogues and Errors

    Oct 12, 2026Boya Zhang, Xilin Dai, Yilin Wang +4Time Series ForecastingTime-Series Foundation Models

    Shanghai Artificial Intelligence Laboratory · Shanghai Jiao Tong University · The Chinese University of Hong Kong

  5. SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting

    Oct 8, 2026Van Dai Do, Huu Hiep Nguyen, Minh Hoang Nguyen +1Multivariate Time Series ForecastingSequence Prediction

    Deakin’s Applied Artificial Intelligence Initiative Deakin University, Geelong, Australia

  6. FreshCast: Timely and Complementary Retrieval for Frozen Time Series Forecasters

    Oct 6, 2026Chao He, Jianyu Xu, Xinyi Guo +5Non-Stationary Time Series ForecastingRetrieval-Augmented Time Series Forecasting

    Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Foshan, China · School of Artificial Intelligence, South China Normal University, Foshan, China · Faculty of Humanities and Arts, Macau University of Science and Technology, Macau, China

  7. GRAM: Correcting Frozen Time-Series Foundation Models via Graph-Retrieved Amplitude Memory

    Oct 4, 2026Xiaoyun Yu, Xiangfei Qiu, Yonggui Huang +7Time Series ForecastingRetrieval-Augmented Time Series Forecasting

    East China Normal University · Peking University · The Chinese University of Hong Kong +3

  8. TIMBRE: Teaching Time Series Forecasters to Read, Remember, and Reconcile

    Oct 3, 2026Xinyu Guan, Zhirong Zhang, Hongyuan Liu +4Time Series ForecastingRetrieval-Augmented Time Series Forecasting

    Alibaba Group · Chang’an University · University of Electronic Science and Technology of China +4

  9. SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

    Oct 2, 2026Mingtian Tan, Palash Goyal, Mihir Parmar +6Time Series ForecastingExogenous Time Series Forecasting

    Google Cloud AI Research · University of Virginia

  10. Dual-Context Analog Retrieval for Time Series Forecasting

    Oct 2, 2026Jung Min Choi, Ngoc Son Le, Ibram Abdelmalak +2Long-Term Time Series ForecastingTime Series Forecasting

    ISMLL, University of Hildesheim · VWFS Data Analytics Research Center (VWFS-DARC), Hildesheim, Germany

  11. GNA: Granular Neighbor Assembly for Retrieval-Augmented Multivariate Time-Series Forecasting

    Sep 28, 2026Vincent UhseMultivariate Time Series ForecastingTime Series Forecasting

    CERN

  12. QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

    Sep 28, 2026Hanyin Cheng, Linfeng Wang, Zhengbo Qu +7Multivariate Time Series ForecastingMultimodal Foundation Models

    East China Normal University · Huawei Technologies Co., Ltd.

  13. Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs

    Sep 19, 2026Daeun Ji, Minkyoung Kim, Dongkuk Kim +3LLM PromptingLLM-Based Time Series Forecasting

    Graduate School of Information, Yonsei University, Seoul, Republic of Korea

  14. Knowledge-Graph-Augmented Chronos-2 for HEC-RAS Surrogate Forecasting

    Sep 18, 2026Edward Holmberg, Elias Ioup, Mahdi AbdelguerfiSurrogate ModelingFlood Forecasting

    Canizaro-Livingston Gulf States Center for Environmental Informatics New Orleans, LA, USA · Center for Geospatial Sciences Naval Research Laboratory Stennis Space Center, Mississippi, USA

  15. Memory in Deep Time-Series Models

    Sep 5, 2026Minh Hoang Nguyen, Huu Hiep Nguyen, Manh Nguyen +3Memory-Augmented Neural NetworksSequence Modeling

    Deakin Applied AI Initiative, Deakin University, Geelong, VIC, Australia

  16. RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting

    Sep 3, 2026Yuchen He, Yueyang Cang, Zhiyuan Ning +2Multivariate Time Series ForecastingResidual Learning

    Department of Automation, Tsinghua University · State Key Laboratory of Hydroscience and Engineering, Tsinghua University

  17. Which Histories Matter for Time Series Forecasting? Learning Predictive Relevance with Future Supervision

    Aug 24, 2026Yong-Hoon Choi, Kwang-Hyun Park, Youngjin ChoLearning to RankTime Series Forecasting

    Division of Robotics, Kwangwoon University Seoul 01897, Republic of Korea

  18. Model-agnostic Retrieval-Augmented Extended Forecasting for time series

    Aug 14, 2026Juan Pablo Villa Serna, Rohan Asthana, Vasileios BelagiannisTime Series ForecastingRetrieval-Augmented Time Series Forecasting

    Friedrich-Alexander-Universität Erlangen–Nürnberg

  19. KReF: Training-Free Retrieval for Long-Term Time-Series Forecasting and Predictive Uncertainty

    Aug 7, 2026Yang Zhang, Rui SuLong-Term Time Series ForecastingRetrieval-Augmented Time Series Forecasting

  20. TS-RAG: Retrieval Augmented Generation for Time Series Forecasting

    Aug 6, 2026Yixiong Xiao, Congxi Xiao, Jingbo ZhouRetrieval-Augmented GenerationTime Series Forecasting

    Baidu, Inc. Beijing, China

  21. Align-RAG: Alignment Is All You Need for TSFM In-Context Learning

    Aug 6, 2026Mohammad Asadi, Soheil Hor, Bardiya Akhbari +6Zero-Shot Time Series ForecastingRetrieval-Augmented ICL

    1Stanford University 2Amazon

  22. CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting

    Aug 4, 2026Xiaoyu Tao, Mingyue Cheng, Bokai Pan +6Time Series ForecastingLLM-Based Time Series Forecasting

    State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China, Hefei, Anhui Province, China

  23. TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion

    Jul 31, 2026Yu Sun, Yuan Chang, Xiaohou Shi +1Multivariate Time Series ForecastingLong-Term Time Series Forecasting

    Beijing University of Posts and Telecommunications Beijing, China · China Telecom Research Institute Beijing, China

  24. FinAbstain: Uncertainty-Calibrated Multimodal RAG for Selective Financial Forecasting

    Jul 27, 2026Dorothy Torres, Wei Cheng, Henan HuangSelective PredictionFinancial Forecasting

    School of Science, Technology, Engineering and Mathematics 263 Academy Street, Room S204 Jersey City, NJ 07306 · School of Electrical Engineering and Computer Science The Pennsylvania State University 207 Electrical Engineering West University Park, PA 16802, USA

  25. PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling

    Jul 22, 2026Shiyuan Luo, Runlong Yu, Chonghao Qiu +6Time Series ForecastingAdaptive Retrieval

    University of Pittsburgh · University of Alabama · University of Minnesota +3

  26. The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting

    Jul 14, 2026Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan KurbanTime Series ForecastingRetrieval-Augmented Time Series Forecasting

    Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA · College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

  27. ReDiTT: Retrieval Augmented Conditional Diffusion Transformers for Asynchronous Time Series

    Jul 14, 2026Saiyue Lyu, Zhitian Zhang, Ruizhi Deng +1Irregular Time-Series ModelingEvent Time Prediction

    Department of Computer Science, University of British Columbia · Work done during an internship at RBC Borealis. · RBC Borealis

  28. PARA-PV: Physics-Aware Retrieval-Augmented PV Prediction Based on Frozen Foundation Model and Distribution Shift Correction

    Jul 9, 2026Hang Fan, Weican Liu, Ying Lu +3Time Series ForecastingNon-Stationary Time Series Forecasting

    School of Economics and Management, North China Electric Power University, 102206, Beijing, China · School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, 50 Nanyang Avenue, Singapore · Department of Electrical Engineering, Tsinghua University, 100084, Beijing, China

  29. Leakage-Aware Benchmarking of LLM Forecasting: Real-Time Nowcasts as the Decision-Time Input for Macro Factor Ranking

    Jun 21, 2026Mao Guan, Qian ChenLearning to RankLook-Ahead Bias in Language Models

    Independent Researcher.

  30. Spectral Retrieval-Augmented Time-Series Forecasting

    Jun 17, 2026Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen +1Frequency-Domain Time Series ModelingNon-Stationary Time Series Forecasting

    Applied Artificial Intelligence Initiative Deakin University Geelong, Australia