Problem
Research questions and friction points this paper is trying to address.
Generative Media
Dynamic Media
Context-Dependent Regeneration
Live Data
Cross-Modal Coherence
Live Artifacts: Authoring Dynamic Media via Live Layers Encapsulating Generative Specifications
🤖 AI Summary
该研究提出Live Artifacts，通过封装生成逻辑来创建动态媒体，使用LiveCanvas系统让创作者在视觉画布中管理动态行为和生成持久性。
📝 Abstract
We frame Live Artifacts as a class of persistent generative media between static assets and interactive software. Unlike conventional generative outputs that collapse into static files, Live Artifacts retain their generative logic as a persistent media property, enabling continuous context-dependent regeneration. Time, location, or live data become part of their generative specifications, initiating coordinated updates across modalities (e.g., adapting text, visuals, and audio together) while preserving composition, semantics, identity, and cross-modal coherence. To facilitate experimentation with this medium, we present LiveCanvas, an authoring system that reconceptualizes visual layers as live generative specifications with explicit mutability and constrained dependencies. Creators orchestrate dynamic behaviors and manage generative persistence within a visual canvas rather than through programming, defining what remains stable, what can change, and how changes propagate. We evaluate Live Artifacts through a gallery of responsive examples and a qualitative study with six professionals, finding that LiveCanvas facilitates a shift from composing static outputs to crafting responsive generative artifacts while remaining aligned with familiar authoring practices.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Live Artifacts
generative media
persistent media property
LiveCanvas
dynamic regeneration
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