6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
XLBench: A Benchmark for Extremely Long Context Understanding with Long-range Dependencies
Xuanfan Ni, Hengyi Cai, Xiaochi Wei +3
Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks but are constrained by their small context window sizes. Various efforts have been propos…
cs.CR2024★ 6 cited
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
Shenglai Zeng, Jiankun Zhang, Pengfei He +8
Retrieval-augmented generation (RAG) is a powerful technique to facilitate language model with proprietary and private data, where data privacy is a pivotal concern. Whereas extens…