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MotionRFT: Unified Reinforcement Fine-Tuning for Text-to-Motion Generation
Text-to-motion generation has advanced with diffusion- and flow-based generative models, yet supervised pre-training remains insufficient to align models with high-level objectives such as semantic consistency, realism, and human preference. Existing post-training methods have key limitations: they
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