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Georgia Institute of Technology
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Achieving robust sim-to-real transfer, this framework allows robots to learn dexterous skills directly from human videos, outperforming traditional methods.
By iteratively challenging LLMs with adaptively generated test cases, this low-code platform co-optimizes code and tests, bypassing the need for manual prompt engineering and boosting reliability in AI-for-Science workflows.
