The argument posits that 21st-century scientific literature acts as toxic training data due to inherent biases, half-truths, and stylistic inconsistencies. This lack of data integrity may degrade the reliability of LLMs trained on academic corpora.
HOW THIS AFFECTS YOU
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researcherYou should consider the potential for bias and misinformation when fine-tuning models on scientific datasets.