PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition

Paper recorded by Signals 4 on 2026-10-14 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-14 on arXiv · recorded by Signals 4 on 2026-10-15

Category: cs.AI · 人工智能 · first seen 2026-10-15

Abstract

3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence in foundation models. Previous methods either leverage large language models to directly predict object coordinates, or utilize generative diffusion priors to synthesize composite images for visual alignment, both of which rely on static priors in di

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