A two-stage agentic RL framework with LLM-generated, iteratively refined reward programs improves functional constraint fidelity in 3D scene generation and enables self-augmentation of the base generator.
Graph-to-3d: End-to-end generation and ma- nipulation of 3d scenes using scene graphs, 2021
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iARCS: Iterative Agentic RL for Controllable 3D Scene Generation
A two-stage agentic RL framework with LLM-generated, iteratively refined reward programs improves functional constraint fidelity in 3D scene generation and enables self-augmentation of the base generator.