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20222026
most citedCode Search based on Context-aware Code Translation

56 citations · 118 across the 24 of their papers we have counts for

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8 papers · 1 filter

cs.CR2026

Understanding and Improving Model Editing for Secure Code Generation

Weifeng Sun, Quanjun Zhang, Yuchen Chen +3

Large language models (LLMs) are widely used for code generation, yet they can reproduce vulnerable implementations learned from insecure training patterns. Prior work has mainly e…

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

Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets

Yuan Xiao, Jiaming Wang, Yuchen Chen +8

The widespread availability of large-scale code datasets has accelerated the development of code large language models (CodeLLMs), raising concerns about unauthorized dataset usage…

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.CR2025★ 1 cited

DeCoMa: Detecting and Purifying Code Dataset Watermarks through Dual Channel Code Abstraction

Yuan Xiao, Yuchen Chen, Shiqing Ma +7

Watermarking is a technique to help identify the source of data points, which can be used to help prevent the misuse of protected datasets. Existing methods on code watermarking, l…

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…