IR-Cocktail/bert-large-uncased-mean-v3-msmarco
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Cocktail, a comprehensive benchmark designed to evaluate Information Retrieval (IR) models amidst the evolving landscape of AI-generated content (AIGC). In an era dominated by Large Language Models (LLMs), the traditional IR corpus, previously solely composed of human-written texts, has expanded to include a significant proportion of LLM-generated content. Cocktail emerges as a valuable resource to response to this transformation, aiming to provide a robust framework for assessing the performance and bias of IR models in handling mixed corpora in this LLM era.