Maru: Information Architecture as a Shared Language for Generating Aligned and Persistent User Interfaces

2026-08-26

AI Summary

论文提出使用信息架构作为共享语言，通过捕捉用户偏好并持久化，解决生成用户界面与用户需求不一致的问题。

Abstract

Generative user interfaces (GenUIs) promise on-demand components tailored to users' needs. As users iterate on information tasks, they construct personal structures over information they encounter---how items are grouped, what gets prioritized, and what terms mean in their context. Yet, current systems leave these structural decisions to the model at each generation, ignoring the structural logic users have established. Without a persistent representational structure shared between user and system, GenUIs have no basis to remain aligned with what users have established. We draw on Information Architecture (IA), a design practice for organizing and structuring information, as a shared language to bridge user-constructed structure and system generation. We present a framework identifying four IA elements---partition, hierarchy, order, and vocabulary---and characterize how each maps to concrete UI generation decisions. We instantiate this framework in Maru, a conversational system that captures user prompts and interactions as IA preferences, persisting as rules both user and system draw on across generations. A user study revealed that IA persistence kept generated UIs aligned as sessions progressed, while alignment without it degraded, with diverse patterns emerging across users and contexts, pointing to the value of IA persistence in aligning GenUI to individual needs.

Problem

• Generative User Interfaces
• Information Architecture
• User Alignment
• Persistent Structure
• Personal Information Needs

Innovation

• Information Architecture
• GenUIs
• Alignment
• Persistence