•RAG-original:此变体是在自然问题数据集上经过微调的模型,尚未进行特定领域的适配。 •RAG-end2end:作为RAG-original的进阶版,该模型针对SQuAD领域进行了进一步的微调,以实现领域适配。 Blended RAG:我们的Blended RAG变体独树一帜,未在SQuAD数据集或相关语料库上进行训练。它结合了优化的字段选择和语义索引的混...
RAG在NQ数据集上的评估 讨论 稀疏与密集向量索引之间的权衡 没有元数据的混合检索器 结论 原文地址 当前RAG系统的局限性 目前在RAG流程中采用的多数检索方法依赖于关键词搜索和相似性搜索,这可能会影响RAG系统的整体准确度。表1总结了目前检索器准确度的基准数据。 表1 | 当前检索器基准 尽管过去提高RAG准确度的努...
我们的研究对先前工作中的三种RAG流程变体进行了对比分析,采用精确匹配(EM)和F1分数作为评估指标,衡量答案生成的准确度,同时考量检索准确度的前5和前10名。 对照组RAG Pipeline · RAG-original:此变体是在自然问题数据集上经过微调的模型,尚未进行特定领域的适配。 · RAG-end2end:作为RAG-original的进阶版,该模型...
通过上述方法,Blended RAG在多个数据集上取得了显著的性能提升。特别是在NQ数据集上,Blended RAG实现了88.77%的top-10检索准确率,超越了现有方法。此外,在TREC-COVID数据集上,Blended RAG也展现了其在不同相关性评分下的有效性。在SqUAD数据集上,Blended RAG在没有经过特定数据集微调的情况下,仍然表现出了较高的...
TABLE IV: Evaluation of the RAG Pipeline on the SquAD Dataset Model/PipelineEMF1Top-5Top-20 RAG-original28.1239.4259.6472.38 RAG-end2end40.0252.6375.7985.57 Blended RAG57.6368.494.8998.58 TABLE V: Evaluation of the RAG pipeline on the NQ dataset ...
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The post--test was applied by the end of teaching the assigned unit. Data was statistically analyzed. Results have been discussed. Based on results, recommendations and suggestions have been occurred.Dr. Bashayer Raghian Albalawi
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