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GEPA (Generalized Evolutionary Prompt Adaptation) is an optimization framework that introduces evolutionary algorithm concepts into AI prompt engineering, screening for the optimal prompt configuration through the generation, evaluation, and elimination of candidate prompts.
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9/12/2026
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UnverifiedGEPA将遗传算法的变异操作与Agent执行轨迹深度绑定,根据轨迹中的具体失败点提出针对性修改而非随机变异75% similarUnverified进化算法是受达尔文自然选择启发的优化方法,自20世纪60年代起被用于解决复杂优化问题61% similarUnverifiedGNoME采用主动学习策略,迭代式地生成候选、预测稳定性、筛选最有价值结构送入DFT计算验证,再更新模型60% similarUnverifiedThe core mechanism of reflective prompt evolution is to have an LLM generate natural language reflections based on task execution results and feed them back into the prompt to form an iterative optimization loop; representative works include APE, EvoPrompt, and Reflexion.59% similarVerifiedPrompt Engineering refers to the practice of carefully designing input prompts for large language models with the goal of guiding the model to generate high-quality, expected outputs.58% similar
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