activity
20202026
most citedRelphormer: Relational Graph Transformer for Knowledge Graph Representations

57 citations · 263 across the 34 of their papers we have counts for

collaborators
Showing 2025Show all

6 papers · 1 filter

cs.CR2025

From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs

Guangyu Shen, Siyuan Cheng, Xiangzhe Xu +4

Large Language Models (LLMs) can acquire deceptive behaviors through backdoor attacks, where the model executes prohibited actions whenever secret triggers appear in the input. Exi…

cs.CR2025

ASTRA: Autonomous Spatial-Temporal Red-teaming for AI Software Assistants

Xiangzhe Xu, Guangyu Shen, Zian Su +9

AI coding assistants like GitHub Copilot are rapidly transforming software development, but their safety remains deeply uncertain-especially in high-stakes domains like cybersecuri…

cs.CR2025

SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks

Kaiyuan Zhang, Siyuan Cheng, Hanxi Guo +8

Large language models (LLMs) have achieved remarkable success and are widely adopted for diverse applications. However, fine-tuning these models often involves private or sensitive…

cs.SE2025★ 1 cited

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

Hanxi Guo, Siyuan Cheng, Kaiyuan Zhang +2

Large language models (LLMs) have become integral to modern software development, producing vast amounts of AI-generated source code. While these models boost programming productiv…

cs.CV2025

CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI

Siyuan Cheng, Lingjuan Lyu, Zhenting Wang +2

With the rapid advancement of generative AI, it is now possible to synthesize high-quality images in a few seconds. Despite the power of these technologies, they raise significant…

cs.LG2025★ 4 cited

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling

Kaiyuan Zhang, Siyuan Cheng, Guangyu Shen +5

Federated learning collaboratively trains a neural network on a global server, where each local client receives the current global model weights and sends back parameter updates (g…