151 citations · 237 across the 11 of their papers we have counts for
12 papers
Runtime Backdoor Detection for Federated Learning via Representational Dissimilarity Analysis
Xiyue Zhang, Xiaoyong Xue, Xiaoning Du +3
Federated learning (FL), as a powerful learning paradigm, trains a shared model by aggregating model updates from distributed clients. However, the decoupling of model learning fro…
SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Covers
Guangke Chen, Yedi Zhang, Fu Song +3
Singing voice conversion (SVC) automates song covers by converting a source singing voice from a source singer into a new singing voice with the same lyrics and melody as the sourc…
CodeMark: Imperceptible Watermarking for Code Datasets against Neural Code Completion Models
Zhensu Sun, Xiaoning Du, Fu Song +1
Code datasets are of immense value for training neural-network-based code completion models, where companies or organizations have made substantial investments to establish and pro…
Source Code Data Augmentation for Deep Learning: A Survey
Terry Yue Zhuo, Zhou Yang, Zhensu Sun +5
The increasingly popular adoption of deep learning models in many critical source code tasks motivates the development of data augmentation (DA) techniques to enhance training data…
Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems
Zhensu Sun, Xiaoning Du, Fu Song +4
Currently, large pre-trained language models are widely applied in neural code completion systems. Though large code models significantly outperform their smaller counterparts, aro…
On the Importance of Building High-quality Training Datasets for Neural Code Search
Zhensu Sun, Li Li, Yan Liu +1
The performance of neural code search is significantly influenced by the quality of the training data from which the neural models are derived. A large corpus of high-quality query…