Guangyu Shen

AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation

2019 · arXiv (Cornell University)

Due to the inherent robustness of segmentation models, traditional norm-bounded attack methods show limited effect on such type of models. In this paper, we focus on generating unrestricted adversarial examples for semantic segmentation models. We …

Constrained Optimization with Dynamic Bound-scaling for Effective NLPBackdoor Defense

2022 · arXiv (Cornell University)

We develop a novel optimization method for NLPbackdoor inversion. We leverage a dynamically reducing temperature coefficient in the softmax function to provide changing loss landscapes to the optimizer such that the process gradually focuses on …

BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense

2023 · arXiv (Cornell University)

Deep Learning backdoor attacks have a threat model similar to traditional cyber attacks. Attack forensics, a critical counter-measure for traditional cyber attacks, is hence of importance for defending model backdoor attacks. In this paper, we …

CodeMirage: A Multi-Lingual Benchmark for Detecting AI-Generated and Paraphrased Source Code from Production-Level LLMs

2025 · arXiv (Cornell University)

Large language models (LLMs) have become integral to modern software development, producing vast amounts of AI-generated source code. While these models boost programming productivity, their misuse introduces critical risks, including code plagiarism, license violations, and …