Charts as Epistemic Actions for Experience-Driven Agentic Data Analysis
[Sztuczna inteligencja] Autorzy: Xinzhe Wang, Xudong Weng, Zang Li i 1 więcej
Data agents built on ReAct-style loops now execute complex analytical workflows over structured data, yet their intermediate reasoning still runs almost entirely through text. Human analysts instead move between numbers, tables, and charts, reading visual evidence to expose trends and anomalies that text summaries drop. We ask whether charts can serve as internal epistemic actions inside a data agent's reasoning loop, and how to teach an agent to use them. We first build \probe{}, a suite of 200 controlled tasks under four matched interface conditions, and find a persistent gap between what agents can read and what they choose to use. Agents score as well from self-generated charts as from numeric output, yet plotting access alone does not translate into consistent use. Task slices show that charts lead on temporal, pattern, and anomaly reasoning, while text leads on precise reading and…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja