most citedLarge Language Models in Fault Localisation

20 citations · 21 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20241 cited

HCPM: Hierarchical Candidates Pruning for Efficient Detector-Free Matching

Ying Chen, Yong Liu, Kai Wu +5

Deep learning-based image matching methods play a crucial role in computer vision, yet they often suffer from substantial computational demands. To tackle this challenge, we presen…

cs.CL2024

Parameter-Efficient Conversational Recommender System as a Language Processing Task

Mathieu Ravaut, Hao Zhang, Lu Xu +2

Conversational recommender systems (CRS) aim to recommend relevant items to users by eliciting user preference through natural language conversation. Prior work often utilizes exte…

eess.IV2024

Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices

Hongye Zeng, Ke Zou, Zhihao Chen +10

Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the mod…

cs.SE202320 cited

Large Language Models in Fault Localisation

Yonghao Wu, Zheng Li, Jie M. Zhang +3

Large Language Models (LLMs) have shown promise in multiple software engineering tasks including code generation, program repair, code summarisation, and test generation. Fault loc…

stat.CO2023

Extended ADMM for general penalized quantile regression with linear constraints in big data

Yongxin Liu, Peng Zeng

Quantile regression (QR) can be used to describe the comprehensive relationship between a response and predictors. Prior domain knowledge and assumptions in application are usually…

cs.LG2023

Exploring Adversarial Attacks on Neural Networks: An Explainable Approach

Justus Renkhoff, Wenkai Tan, Alvaro Velasquez +7

Deep Learning (DL) is being applied in various domains, especially in safety-critical applications such as autonomous driving. Consequently, it is of great significance to ensure t…