QuiZSF: An efficient data-model interaction framework for zero-shot time-series forecasting Article Swipe

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Qihe Huang , Bin‐Wu Wang , Kuo Yang , Huan Li , Yan Wang · YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2508.06915

Time series forecasting has become increasingly important to empower diverse applications with streaming data. Zero-shot time-series forecasting (ZSF), particularly valuable in data-scarce scenarios, such as domain transfer or forecasting under extreme conditions, is difficult for traditional models to deal with. While time series pre-trained models (TSPMs) have demonstrated strong performance in ZSF, they often lack mechanisms to dynamically incorporate external knowledge. Fortunately, emerging retrieval-augmented generation (RAG) offers a promising path for injecting such knowledge on demand, yet they are rarely integrated with TSPMs. To leverage the strengths of both worlds, we introduce RAG into TSPMs to enhance zero-shot time series forecasting. In this paper, we propose QuiZSF (Quick Zero-Shot Time Series Forecaster), a lightweight and modular framework that couples efficient retrieval with representation learning and model adaptation for ZSF. Specifically, we construct a hierarchical tree-structured ChronoRAG Base (CRB) for scalable time-series storage and domain-aware retrieval, introduce a Multi-grained Series Interaction Learner (MSIL) to extract fine- and coarse-grained relational features, and develop a dual-branch Model Cooperation Coherer (MCC) that aligns retrieved knowledge with two kinds of TSPMs: Non-LLM based and LLM based. Compared with contemporary baselines, QuiZSF, with Non-LLM based and LLM based TSPMs as base model, respectively, ranks Top1 in 75% and 87.5% of prediction settings, while maintaining high efficiency in memory and inference time.

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preprint

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en

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http://arxiv.org/abs/2508.06915

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https://arxiv.org/pdf/2508.06915

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green

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https://openalex.org/W4416178479

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https://openalex.org/W4416178479

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DOI

https://doi.org/10.48550/arxiv.2508.06915

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Title

QuiZSF: An efficient data-model interaction framework for zero-shot time-series forecasting

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preprint

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en

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2025

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2025-08-09

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Qihe Huang, Bin‐Wu Wang, Kuo Yang, Huan Li, Yan Wang

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https://arxiv.org/abs/2508.06915

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https://arxiv.org/pdf/2508.06915

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Yes

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green

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