MiXR enables in-situ 3D design by harvesting real-world geometry for user-defined compositions that generative AI then refines, outperforming text-only generative methods in control and fidelity per a 12-person study.
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Post-generation control in AI-assisted math visual creation yields higher teacher ratings for predictability and correctness than pre- or mid-generation control, with qualitative trade-offs in agency and effort.
Elemental Alchemist generates contextual tools and abstracts particle-system parameters into semantic mid-level attributes and high-level conceptual controls, with a user study indicating it helps practitioners translate creative goals into technical edits.
citing papers explorer
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MiXR: Harvesting and Recomposing Geometry from Real-World Objects for In-Situ 3D Design
MiXR enables in-situ 3D design by harvesting real-world geometry for user-defined compositions that generative AI then refines, outperforming text-only generative methods in control and fidelity per a 12-person study.
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When Should Teachers Control AI Generation for Mathematics Visuals?
Post-generation control in AI-assisted math visual creation yields higher teacher ratings for predictability and correctness than pre- or mid-generation control, with qualitative trade-offs in agency and effort.
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Elemental Alchemist: A Generative Interface for Semantic Control of Particle Systems Across Dynamic Levels of Abstraction
Elemental Alchemist generates contextual tools and abstracts particle-system parameters into semantic mid-level attributes and high-level conceptual controls, with a user study indicating it helps practitioners translate creative goals into technical edits.