106 citations · 197 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation
Zhijie Wang, Zhehua Zhou, Jiayang Song +3
The rapid advancement of generative AI and multi-modal foundation models has shown significant potential in advancing robotic manipulation. Vision-language-action (VLA) models, in…
Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
Zhijie Wang, Zijie Zhou, Da Song +4
Large Language Models (LLMs) have demonstrated unprecedented capabilities in code generation. However, there remains a limited understanding of code generation errors that LLMs can…
TESTEVAL: Benchmarking Large Language Models for Test Case Generation
Wenhan Wang, Chenyuan Yang, Zhijie Wang +6
Testing plays a crucial role in the software development cycle, enabling the detection of bugs, vulnerabilities, and other undesirable behaviors. To perform software testing, teste…
MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems
Xinyu Gao, Zhijie Wang, Yang Feng +3
Multi-sensor fusion stands as a pivotal technique in addressing numerous safety-critical tasks and applications, e.g., self-driving cars and automated robotic arms. With the contin…
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…