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National Chengchi University
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ConcoLixir boosts Python concolic testing coverage by leveraging LLMs to intelligently navigate semantic barriers and library boundaries.
Reducing optimization calls by up to 66% without sacrificing tracking accuracy could revolutionize real-time control for soft robotics.
Train a text-to-image model that rivals the state-of-the-art with 1/5th the compute by using GPT-4 to generate better captions.
