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20232026
most citedDefending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss

2 citations · 2 across the 6 of their papers we have counts for

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Showing 2024Show all

3 papers · 1 filter

cs.SE2024

SimADFuzz: Simulation-Feedback Fuzz Testing for Autonomous Driving Systems

Huiwen Yang, Yu Zhou, Taolue Chen

Autonomous driving systems (ADS) have achieved remarkable progress in recent years. However, ensuring their safety and reliability remains a critical challenge due to the complexit…

cs.SE2024

Anchor Attention, Small Cache: Code Generation with Large Language Models

Xiangyu Zhang, Yu Zhou, Guang Yang +2

The development of large language models (LLMs) has revolutionized automated code generation. However, their high demand of computation resources has hindered a broader deployment…

cs.CR2024★ 2 cited

Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss

Guang Yang, Yu Zhou, Xiang Chen +4

Code Language Models (CLMs), particularly those leveraging deep learning, have achieved significant success in code intelligence domain. However, the issue of security, particularl…