AION: Next-Generation Tasks and Practical Harness for Time Series
The paper titled 'AION: Next-Generation Tasks and Practical Harness for Time Series' presents a new framework for time series research. It emphasizes the need for realistic tasks that integrate prediction and contextual reasoning, moving away from traditional fixed benchmarks. The authors introduce AION, a harness designed to enhance the capabilities of agents in time series analysis through structured decision support and temporal grounding.
- ▪The AION framework consists of three components: a task file, a workspace, and a validation interface.
- ▪AION incorporates six component groups including agents, skills, and evaluation mechanisms.
- ▪A case study using Kaggle Store Sales demonstrates that AION produces more detailed process traces and review steps compared to traditional methods.
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Computer Science > Artificial Intelligence arXiv:2605.25045 (cs) [Submitted on 24 May 2026] Title:AION: Next-Generation Tasks and Practical Harness for Time Series Authors:Tianxiang Zhan, Xiaobao Song, Tong Guan, Shirui Pan, Ming Jin View a PDF of the paper titled AION: Next-Generation Tasks and Practical Harness for Time Series, by Tianxiang Zhan and 4 other authors View PDF Abstract:Time series research is moving beyond fixed forecasting benchmarks toward realistic tasks that combine prediction, contextual reasoning, tool use, and structured decision support. Most benchmarks are built around clean data and short evaluation loops; agents alone may miss temporal constraints, evidence checks, or review before finalizing outputs.
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