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20242026
most citedSecurity of Language Models for Code: A Systematic Literature Review

5 citations · 7 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CR2026

Breaking Customized LLMs for Coding: Automated Red Teaming for Instruction Backdoor Attacks

Yuchen Chen, Wei Cheng, Yuan Xiao +5

LLM customization platforms allow users to build task-specific models for code intelligence tasks by embedding instructions into system prompts, without modifying the underlying mo…

cs.CR2026

Insecure Coding Preferences in Long-Term Memory: Security Risks for LLM-based Code Generation

Yuchen Chen, Wei Cheng, Yuan Xiao +7

LLM-based systems increasingly incorporate long-term memory to improve cross-session continuity. However, once insecure coding preferences are stored, they may silently influence s…

cs.CR2026

Securing Code Understanding: Detecting Natural Backdoor Vulnerability in Code Language Models

Yuchen Chen, Weisong Sun, Haocheng Huang +11

Code Language Models (CodeLMs) have become integral to software engineering, significantly advancing code intelligence tasks. However, their widespread adoption has raised critical…

cs.CR2026

DuCodeMark: Dual-Purpose Code Dataset Watermarking via Style-Aware Watermark-Poison Design

Yuchen Chen, Yuan Xiao, Chunrong Fang +2

The proliferation of large language models for code (CodeLMs) and open-source contributions has heightened concerns over unauthorized use of source code datasets. While watermarkin…

cs.CR2024★ 1 cited

Eliminating Backdoors in Neural Code Models for Secure Code Understanding

Weisong Sun, Yuchen Chen, Chunrong Fang +7

Neural code models (NCMs) have been widely used to address various code understanding tasks, such as defect detection. However, numerous recent studies reveal that such models are…