Schemex: Interactive Structural Abstraction from Examples with Contrastive Refinement
Sitong Wang, Samia Menon, Dingzeyu Li, Xiaojuan Ma, Richard Zemel, Lydia B. Chilton
公開日: 2025/4/16
Abstract
Each type of creative or communicative work is underpinned by an implicit structure. People learn these structures from examples - a process known in cognitive science as schema induction. However, inducing schemas is challenging, as structural patterns are often obscured by surface-level variation. We present Schemex, an interactive visual workflow that scaffolds schema induction through clustering, abstraction, and contrastive refinement. Schemex supports users through visual representations and interactive exploration that connect abstract structures to concrete examples, promoting transparency, adaptability, and effective human-AI collaboration. In our user study, participants reported significantly greater insight and confidence in the schemas developed with Schemex compared to those created using a baseline of an AI reasoning model. We conclude by discussing the broader implications of structural abstraction and contrastive refinement across domains.