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Data contamination in Large Language Models (LLMs) is a significant concern that can impact their performance on various tasks. It refers to the presence of test data from downstream tasks in the training data of LLMs. Addressing data contamination is crucial because it can lead to biased results and affect the actual effectiveness of LLMs […] The post The Hidden Influence of Data Contamination on Large Language Models appeared first on Unite.AI.