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This paper analyzes the theoretical framework and mathematically demonstrate that only-latter timestep updates of diffusion model may be harmful for diversity contrary to the conclusions presented in a previous work, and proposes an incremental Feynman-Kac training based on strong theoretical foundations to achieve the...
iARCS is presented, an iterative agentic reinforcement learning framework that adapts a pretrained scene generator to naturallanguage task requirements and shows that data generated by iARCS improves a base generator, supporting its value as a practical synthetic data generation tool rather than only a controllable sce...
SceneBench is introduced, a benchmark of 966 photorealistic 3D scenes reconstructed with Gaussian Splatting and densely annotated with hierarchical semantics spanning scenes, rooms, functional areas, object groups, and individual objects that provides a realistic testbed for developing and evaluating models capable of...
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