Less Is More: Elevating RAG via Performance-Driven Context Compression 事件

Less Is More: Elevating RAG via Performance-Driven Context Compression arXiv:2508.19282v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm for improving the timeliness of knowledge updates and the factual accuracy of large language models. However, incorporating a large volume of retrieved documents significantly increases input length, leading to prohibitive computational costs. Existing compression approaches often compromise task perfo