Zero-Shot Time-Series Question Answering via Decoupled Perception and Reasoning

Excerpt

arXiv:2610.04942v1 Announce Type: new Abstract: Time-series question answering (TSQA) requires grounding linguistic queries and diverse answer formats in complex numerical observations. However, existing methods heavily overfit to specific datasets and struggle to generalize when input series, question contexts, and answer requirements shift simultaneously. To address this challenge, we propose TSHarness, an agentic framework that establishes a decoupled workflow for cross-dataset zero-shot TSQA