Contextualized Dynamic Explanations: A Vision

2026-05-18

AI Summary

Traditional asynchronous, data-driven explanations often fail to effectively convey information due to their lack of audience adaptation and interactivity. To address this limitation, this work proposes the CODEX framework, which introduces autonomous agents into the data explanation process for the first time. By integrating multimodal generation, dynamic audience modeling, and context-aware decision-making mechanisms, CODEX constructs adaptive information interfaces in real time. The framework continuously evaluates interaction progress against predefined communicative intents and dynamically adjusts its explanatory strategies to deliver personalized and highly effective data interpretations. This study establishes both theoretical foundations and methodological support for interactive, context-sensitive, data-driven explanation systems.

Abstract

Asynchronous data-driven explanations often fail because the content and presentation are not tailored to the target audience, and they provide limited opportunities for active audience engagement. We present a vision for Contextualized Dynamic Explanations (CODEX), an agentic approach to dynamically generating contextualized multi-modal information interfaces for effective data-driven explanations based on an evolving audience model and a predefined communication intent. The premise underlying CODEX is that it is impossible for communicators to anticipate the full range of interactive scenarios involving the target audience. This observation motivates a set of research challenges focused on developing autonomous agents capable of evaluating communication progress, making context-sensitive decisions, and producing effective information representations.

Problem

• data-driven explanations
• audience engagement
• contextualization
• asynchronous communication
• explanation effectiveness

Innovation

• Contextualized Dynamic Explanations
• agentic explanation
• audience modeling
• multi-modal interfaces
• adaptive communication