11 citations · 17 across the 9 of their papers we have counts for
9 papers
Neural Federated Learning for Livestock Growth Prediction
Shoujin Wang, Mingze Ni, Wei Liu +6
Livestock growth prediction is essential for optimising farm management and improving the efficiency and sustainability of livestock production, yet it remains underexplored due to…
Cross-Entropy Attacks to Language Models via Rare Event Simulation
Mingze Ni, Yongshun Gong, Wei Liu
Black-box textual adversarial attacks are challenging due to the lack of model information and the discrete, non-differentiable nature of text. Existing methods often lack versatil…
Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial Approach
Jiyao Li, Mingze Ni, Yongshun Gong +1
Deep learning underpins most of the currently advanced natural language processing (NLP) tasks such as textual classification, neural machine translation (NMT), abstractive summari…
SleepNet and DreamNet: Enriching and Reconstructing Representations for Consolidated Visual Classification
Mingze Ni, Wei Liu
An effective integration of rich feature representations with robust classification mechanisms remains a key challenge in visual understanding tasks. This study introduces two nove…
Reversible Jump Attack to Textual Classifiers with Modification Reduction
Mingze Ni, Zhensu Sun, Wei Liu
Recent studies on adversarial examples expose vulnerabilities of natural language processing (NLP) models. Existing techniques for generating adversarial examples are typically dri…
AICAttack: Adversarial Image Captioning Attack with Attention-Based Optimization
Jiyao Li, Mingze Ni, Yifei Dong +2
Recent advances in deep learning research have shown remarkable achievements across many tasks in computer vision (CV) and natural language processing (NLP). At the intersection of…
Frauds Bargain Attack: Generating Adversarial Text Samples via Word Manipulation Process
Mingze Ni, Zhensu Sun, Wei Liu
Recent research has revealed that natural language processing (NLP) models are vulnerable to adversarial examples. However, the current techniques for generating such examples rely…
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…
CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning
Zhensu Sun, Xiaoning Du, Fu Song +2
Github Copilot, trained on billions of lines of public code, has recently become the buzzword in the computer science research and practice community. Although it is designed to he…