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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

collaborators

6 papers

cs.CL2026

SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD

Dongfang Li, Xiaodong Luo, Ruoyu Sun +62

Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pre…

cs.SE2025

CODE-DITING: A Reasoning-Based Metric for Functional Alignment in Code Evaluation

Guang Yang, Yu Zhou, Xiang Chen +5

Trustworthy evaluation methods for code snippets play a crucial role in neural code generation. Traditional methods, which either rely on reference solutions or require executable…

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…

cs.SE2023

Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models

Guang Yang, Yu Zhou, Xiang Chen +3

Large Language Models (LLMs) have demonstrated remarkable potential in code generation. The integration of Chain of Thought (CoT) reasoning can further boost their performance. How…