4 citations · 6 across the 7 of their papers we have counts for
8 papers
Characterizing the Landscape of Open-Source Satellite Software
Jinfeng Wen, Qi Liang, Yuehan Sun +4
Satellites have become fundamental components of modern technological systems, supporting critical infrastructure in communication, navigation, Earth observation, and scientific re…
LLMs Are Not a Silver Bullet: A Case Study on Software Fairness
Xinyue Li, Sixuan Li, Ying Xiao +4
Fairness is a critical requirement for human-related, high-stakes software systems, motivating extensive research on bias mitigation. Prior work has largely focused on tabular data…
BAMAS: Structuring Budget-Aware Multi-Agent Systems
Liming Yang, Junyu Luo, Xuanzhe Liu +2
Large language model (LLM)-based multi-agent systems have emerged as a powerful paradigm for enabling autonomous agents to solve complex tasks. As these systems scale in complexity…
A First Look at Bugs in LLM Inference Engines
Mugeng Liu, Siqi Zhong, Weichen Bi +5
Large language model-specific inference engines (in short as \emph{LLM inference engines}) have become a fundamental component of modern AI infrastructure, enabling the deployment…
FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation
Junyu Luo, Zhizhuo Kou, Liming Yang +10
Multimodal Large Language Models (MLLMs) have experienced rapid development in recent years. However, in the financial domain, there is a notable lack of effective and specialized…
Promptware Engineering: Software Engineering for Prompt-Enabled Systems
Zhenpeng Chen, Chong Wang, Weisong Sun +3
Large Language Models (LLMs) are increasingly integrated into software applications, giving rise to a broad class of prompt-enabled systems, in which prompts serve as the primary '…
Fairness Testing of Large Language Models in Role-Playing
Xinyue Li, Zhenpeng Chen, Jie M. Zhang +6
Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their p…
Bias Behind the Wheel: Fairness Testing of Autonomous Driving Systems
Xinyue Li, Zhenpeng Chen, Jie M. Zhang +3
This paper conducts fairness testing of automated pedestrian detection, a crucial but under-explored issue in autonomous driving systems. We evaluate eight state-of-the-art deep le…