Contextualized Dynamic Explanations: A Vision
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866913142096789504 |
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| author | Liu, Zhicheng Li, Jason H Briskin, Greg |
| author_facet | Liu, Zhicheng Li, Jason H Briskin, Greg |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_18698 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Contextualized Dynamic Explanations: A Vision Liu, Zhicheng Li, Jason H Briskin, Greg Human-Computer Interaction 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. |
| title | Contextualized Dynamic Explanations: A Vision |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2605.18698 |