mlsanityData to 7 Oct 2026

LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

arXiv 2402.16132 ↗First posted 25 Feb 2024cs.CL cs.AIcited by 56

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Abstract (arXiv)

Time-series forecasting (TSF) finds broad applications in real-world scenarios. Prompting off-the-shelf Large Language Models (LLMs) demonstrates strong zero-shot TSF capabilities while preserving computational efficiency. However, existing prompting methods oversimplify TSF as language next-token predictions, overlooking its dynamic nature and lack of integration with state-of-the-art prompt strategies such as Chain-of-Thought. Thus, we propose LSTPrompt, a novel approach for prompting LLMs in zero-shot TSF tasks. LSTPrompt decomposes TSF into short-term and long-term forecasting sub-tasks, tailoring prompts to each. LSTPrompt guides LLMs to regularly reassess forecasting mechanisms to enhance adaptability. Extensive evaluations demonstrate consistently better performance of LSTPrompt than existing prompting methods, and competitive results compared to foundation TSF models.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). Builds on 20 of its 31 references that are in the map. First posted on arXiv 25 Feb 2024.

Builds on

20 of 31 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  6. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  7. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  8. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  9. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  10. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,020
  11. 2017Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networkscited by 869
  12. 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 744
8 more
  1. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 615
  2. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 491
  3. 2020Time Series Forecasting With Deep Learning: A Surveycited by 457
  4. 2021Monash Time Series Forecasting Archivecited by 256
  5. 2021Pretrained Transformers as Universal Computation Enginescited by 162
  6. 2023Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Modelcited by 145
  7. 2021Darts: User-Friendly Modern Machine Learning for Time Seriescited by 90
  8. 2023Large Pre-trained time series models for cross-domain Time series analysis taskscited by 22

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 13; 2025: 30; 2026: 13.

56 papers.

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  1. 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patternscited by 102
  2. 2024AgentReview: Exploring Peer Review Dynamics with LLM Agentscited by 92
  3. 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancementcited by 74
  4. 2024Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysiscited by 65
  5. 2025Time Series Forecasting via Reasoning: A Slow-Thinking Approach with Reinforcement Fine-Tuned LLMscited by 34
  6. 2024Empowering Time Series Analysis with Foundation Models: A Comprehensive Surveycited by 23
  7. 2024Can LLMs Serve As Time Series Anomaly Detectors?cited by 22
  8. 2024See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzerscited by 20
  9. 2025How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlookcited by 20
  10. 2024TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generationcited by 18
  11. 2025BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modelingcited by 18
  12. 2025A Survey of AIOps in the Era of Large Language Modelscited by 18
38 more
  1. 2025From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretizationcited by 13
  2. 2025Can Multimodal LLMs Perform Time Series Anomaly Detection?cited by 11
  3. 2025AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecastingcited by 11
  4. 2025TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoningcited by 10
  5. 2025MicroRemed: Benchmarking LLMs in Microservices Remediationcited by 10
  6. 2024TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Modelscited by 8
  7. 2026MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoningcited by 8
  8. 2025Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectivescited by 7
  9. 2025TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectivenesscited by 6
  10. 2025FLAIRR-TS -- Forecasting LLM-Agents with Iterative Refinement and Retrieval for Time Seriescited by 6
  11. 2024UniCL: A Universal Contrastive Learning Framework for Large Time Series Modelscited by 5
  12. 2024FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Modelscited by 5
  13. 2025BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecastingcited by 5
  14. 2024ReAugment: Model Zoo-Guided RL for Few-Shot Time Series Augmentation and Forecastingcited by 3
  15. 2025MoTime: A Dataset Suite for Multimodal Time Series Forecastingcited by 3
  16. 2025DELPHYNE: A Pre-Trained Model for General and Financial Time Seriescited by 3
  17. 2026Is More Context Always Better? Examining LLM Reasoning Capability for Time Interval Predictioncited by 3
  18. 2026Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoningcited by 3
  19. 2026E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuningcited by 3
  20. 2024Enhancing Traffic Prediction with Textual Data Using Large Language Modelscited by 2
  21. 2025TOKON: TOKenization-Optimized Normalization for time series analysis with a large language modelcited by 2
  22. 2025In-Context and Few-Shots Learning for Forecasting Time Series Data based on Large Language Modelscited by 2
  23. 2026Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecastingcited by 2
  24. 2024LETS-C: Leveraging Text Embedding for Time Series Classificationcited by 1
  25. 2025Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgmentcited by 1
  26. 2025Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecastingcited by 1
  27. 2025TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecastingcited by 1
  28. 2025UniCast: A Unified Framework for Instance-Conditioned Multimodal Time-Series Forecastingcited by 1
  29. 2025Tackling Time-Series Forecasting Generalization via Mitigating Concept Driftcited by 1
  30. 2026LLM Agents for Time-Series: A Surveycited by 1
  31. 2025Context information can be more important than reasoning for time series forecasting with a large language modelcited by 0
  32. 2025ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Cross-Modal Alignment Datasetcited by 0
  33. 2025From Time Series Analysis to Question Answering: A Survey in the LLM Eracited by 0
  34. 2025StellarF: A Physics-Informed LoRA Framework for Stellar Flare Forecasting with Historical & Statistical Datacited by 0
  35. 2025Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecastingcited by 0
  36. 2025Forecasting Clicks in Digital Advertising: Multimodal Inputs and Interpretable Outputscited by 0
  37. 2025MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Modelscited by 0
  38. 2026CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecastingcited by 0

50 most cited of 56 All 56 (JSON)

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  2. 2024AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
  3. 2026Rethinking the Role of LLMs in Time Series Forecasting
  4. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
  5. 2025Small but Mighty: Enhancing Time Series Forecasting with Lightweight LLMs
  6. 2025Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
  7. 2026OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning
  8. 2025Conversational Time Series Foundation Models: Towards Explainable and Effective Forecasting