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arXiv · 2510.16980

Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision

Kanghui Ning·Zijie Pan·Yushan Jiang·Anderson Schneider·Yuriy Nevmyvaka·Dongjin Song
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Abstract

Time series reasoning is emerging as the next frontier in temporal analysis, aiming to move beyond pattern recognition towards explicit, interpretable, and trustworthy inference. This paper presents a BlueSky vision built on two complementary directions. One builds robust foundations for time series reasoning, centered on comprehensive temporal understanding, structured multi-step reasoning, and faithful evaluation frameworks. The other advances system-level reasoning, moving beyond language-only explanations by incorporating multi-agent collaboration, multi-modal context, and retrieval-augmented approaches. Together, these directions outline a flexible and extensible framework for advancing time series reasoning, aiming to deliver interpretable and trustworthy temporal intelligence across diverse domains.

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Kanghui Ning, Zijie Pan, Yushan Jiang, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song. 2025-10-19. Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision. https://arxiv.org/abs/2510.16980

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