VisTR: Visualizations as Representations for Time-series Table Reasoning

Understand

Time-series table reasoning interprets temporal patterns and relationships in data to answer user queries.

• Despite recent advancements leveraging large language models (LLMs), existing methods often struggle with pattern recognition, context lost in long time-series data, and the lack of visual-based reasoning capabilities.
• To address these challenges, we propose VisTR, a framework that places visualizations at the core of the reasoning process.
• Specifically, VisTR leverages visualizations as representations to bridge raw time-series data and human cognitive processes.