AION: Next-Generation Tasks and Practical Harness for Time Series
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. We first formalize next-generation time series tasks as three-component tuples consisting of a task file, a workspace, and a validation interface. We then present AION, a time series harness built from six component groups: agents, skills, rules, memory, evaluation, and protocols. In this harness, we use three design principles: temporal groundi...
| Authors | Tianxiang Zhan, Xiaobao Song, Tong Guan et al. |
|---|---|
| Primary category | cs.AI |
| Published | 24 May 2026 |
| Last updated at source | 24 May 2026 |
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