19 citations · 26 across the 5 of their papers we have counts for
5 papers
Speculative Coreset Selection for Task-Specific Fine-tuning
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +4
Task-specific fine-tuning is essential for the deployment of large language models (LLMs), but it requires significant computational resources and time. Existing solutions have pro…
Data-centric NLP Backdoor Defense from the Lens of Memorization
Zhenting Wang, Zhizhi Wang, Mingyu Jin +3
Backdoor attack is a severe threat to the trustworthiness of DNN-based language models. In this paper, we first extend the definition of memorization of language models from sample…
Rethinking the Reverse-engineering of Trojan Triggers
Zhenting Wang, Kai Mei, Hailun Ding +2
Deep Neural Networks are vulnerable to Trojan (or backdoor) attacks. Reverse-engineering methods can reconstruct the trigger and thus identify affected models. Existing reverse-eng…
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning
Zhenting Wang, Juan Zhai, Shiqing Ma
Deep neural networks are vulnerable to Trojan attacks. Existing attacks use visible patterns (e.g., a patch or image transformations) as triggers, which are vulnerable to human ins…
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons
Xuanqi Gao, Juan Zhai, Shiqing Ma +3
With Deep Neural Network (DNN) being integrated into a growing number of critical systems with far-reaching impacts on society, there are increasing concerns on their ethical perfo…