
MIT researchers have developed a new technique called HardFlow that allows generative AI models to meet strict safety and task-specific requirements without sacrificing output quality. This method gives models more freedom during the generation process, enforcing constraints only on the final output. It has been tested in applications such as robotics and computer vision, consistently satisfying required constraints while improving solution quality. The technique can be applied to pretrained models without retraining, making it a versatile tool for safety-critical environments.
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