LLM-Based Time Series Forecasting

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Overview

LLM-based time series forecasting studies how language models can predict future values or events from numerical sequences, often enriched with news, clinical notes, weather, or other context. Common approaches map time-series patches or frequency features into frozen or lightly adapted LLMs, combine them with specialized time-series foundation models, or use retrieval and agents to interpret events and revise forecasts; probabilistic decoders and multimodal fusion address uncertainty and heterogeneous inputs. Applications include finance, traffic, energy, epidemics, and healthcare, with evaluations spanning long- and short-horizon accuracy, zero-shot transfer, and benchmarks such as GIFT-Eval and M4. A central tension is that contextual reasoning and pretraining can help under domain shift or sparse data, but numerical forecasters often remain stronger, while reported gains can be vulnerable to leakage and metrics that overlook calibration or tail errors.

Latest papers

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100 papers11 papers in the last four weeks, down 42% on the four weeks before. 0.1% of all new papers.

  1. MM-ISTS: Cooperating Irregularly Sampled Time Series Forecasting with Multimodal Vision-Text LLMs

    Mar 6, 2026Zhi Lei, Chenxi Liu, Hao Miao +3Irregular Time-Series ModelingMultivariate Time Series Forecasting

    East China Normal University, Shanghai, China · Centre for Artificial Intelligence and Robotics, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China · Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

  2. TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts

    Feb 25, 2026Jiafeng Lin, Yuxuan Wang, Huakun Luo +2Time Series TransformersLLM-Based Time Series Forecasting

    School of Software, BNRist, Tsinghua University.

  3. Deep TPC: Temporal-Prior Conditioning for Time Series Forecasting

    Feb 18, 2026Filippos Bellos, NaveenJohn Premkumar, Yannis Avrithis +2LLM-Based Time Series ForecastingLong-Term Time Series Forecasting

    University of Michigan, Ann Arbor, MI, USA · Independent Scientist · Capital One, McLean, VA, USA

  4. Rethinking the Role of LLMs in Time Series Forecasting

    Feb 16, 2026Xin Qiu, Junlong Tong, Yirong Sun +3LLM-Based Time Series ForecastingTime Series Forecasting

    Ningbo Key Laboratory of Spatial Intelligence and Digital Derivative, Institute of Digital Twin, Eastern Institute of Technology, Ningbo · Zhejiang University · LMU Munich

  5. Learning Agentic Time Series Forecasting via Trajectory Distillation and Memory-Based Reinforcement Learning

    Feb 14, 2026Xiaoyu Tao, Mingyue Cheng, Yaguo Liu +4Agentic Time Series ForecastingTime Series Forecasting

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

  6. GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting

    Jan 8, 2026Shovito Barua Soumma, Hassan GhasemzadehTime Series ForecastingBlood Glucose Forecasting

    College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA · School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA

  7. A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs

    Dec 7, 2025Humzah Merchant, Bradford LevyLook-Ahead Bias in Language ModelsLLM-Based Time Series Forecasting

    University of Chicago Chicago, IL 60637

  8. Auditable Context-Aware HFMD Forecasting with Structured LLM Agents

    Nov 28, 2025Joongwon Chae, Runming Wang, Chen Xiong +5Epidemic ForecastingExplainable Time Series Forecasting

    Institute of Biomedicine and Health Engineering, Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China · The First Hospital of Hebei Medical University, Shijiazhuang, China · The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China +1

  9. AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Time Series Forecasting

    Nov 12, 2025Xiaohan Zhang, Tian Gao, Mingyue Cheng +5Time Series ForecastingLLM-Based Time Series Forecasting

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

  10. Markovian Linguistic-Temporal Bridge: Unlocking the Potential of LLMs for Time Series Forecasting

    May 19, 2025Siming Sun, Kai Zhang, Xuejun Jiang +2Time Series ForecastingLLM-Based Time Series Forecasting

    Zhejiang University