Context window management refers to the technique of efficiently handling the limited memory space in AI models to process long inputs. It involves prioritizing relevant data, truncating older tokens, or summarizing content to maintain coherent conversations. Developers, researchers, and users of chatbots or large language models benefit by improving response accuracy, reducing errors, and enabling extended interactions without performance loss.
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