SWE Agent is a research project that presents an inference-time gradient-free method for code generation with large language models. Developed by the Princeton Natural Language Processing group, it aims to improve the efficiency of code generation by eliminating the need for gradients during inference. SWE Agent explores innovative techniques to enhance AI performance in generating accurate and functional code, contributing to advancements in AI-assisted programming.Visit Website
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