8 citations · 11 across the 4 of their papers we have counts for
4 papers
BACKRUNNER: Mitigating Smart Contract Attacks in the Real World
Chaofan Shou, Yuanyu Ke, Yupeng Yang +11
Billions of dollars have been lost due to vulnerabilities in smart contracts. To counteract this, researchers have proposed attack frontrunning protections designed to preempt mali…
LLM4Fuzz: Guided Fuzzing of Smart Contracts with Large Language Models
Chaofan Shou, Jing Liu, Doudou Lu +1
As blockchain platforms grow exponentially, millions of lines of smart contract code are being deployed to manage extensive digital assets. However, vulnerabilities in this mission…
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan +4
Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, t…
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity
Martin Gubri, Maxime Cordy, Mike Papadakis +2
We propose transferability from Large Geometric Vicinity (LGV), a new technique to increase the transferability of black-box adversarial attacks. LGV starts from a pretrained surro…