6 citations · 7 across the 3 of their papers we have counts for
4 papers
Interact-RAG: Reason and Interact with the Corpus, Beyond Black-Box Retrieval
Yulong Hui, Chao Chen, Zhihang Fu +3
Retrieval-Augmented Generation (RAG) has significantly enhanced LLMs by incorporating external information. However, prevailing agentic RAG approaches are constrained by a critical…
OkraLong: A Flexible Retrieval-Augmented Framework for Long-Text Query Processing
Yulong Hui, Yihao Liu, Yao Lu +1
Large Language Models (LLMs) encounter challenges in efficiently processing long-text queries, as seen in applications like enterprise document analysis and financial report compre…
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document Analysis
Yulong Hui, Yao Lu, Huanchen Zhang
The use of Retrieval-Augmented Generation (RAG) has improved Large Language Models (LLMs) in collaborating with external data, yet significant challenges exist in real-world scenar…
Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native
Yao Lu, Song Bian, Lequn Chen +19
In this paper, we investigate the intersection of large generative AI models and cloud-native computing architectures. Recent large models such as ChatGPT, while revolutionary in t…