48 citations · 64 across the 4 of their papers we have counts for
4 papers
Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks
Qiang Ke, Yanjie Zhao, Hongjin Leng +2
While Retrieval-Augmented Generation (RAG) is increasingly adopted to ground Large Language Models (LLMs) in software artifacts, the optimal configuration of its components remains…
Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems
Shengming Zhao, Yuchen Shao, Yuheng Huang +4
Retrieval-Augmented Generation (RAG) has emerged as a critical technique for enhancing large language model (LLM) capabilities. However, practitioners face significant challenges w…
Beyond Fidelity: Explaining Vulnerability Localization of Learning-based Detectors
Baijun Cheng, Shengming Zhao, Kailong Wang +6
Vulnerability detectors based on deep learning (DL) models have proven their effectiveness in recent years. However, the shroud of opacity surrounding the decision-making process o…
Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models
Yuheng Huang, Jiayang Song, Zhijie Wang +4
The recent performance leap of Large Language Models (LLMs) opens up new opportunities across numerous industrial applications and domains. However, erroneous generations, such as…