2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
CodeScore-R: An Automated Robustness Metric for Assessing the FunctionalCorrectness of Code Synthesis
Guang Yang, Yu Zhou, Xiang Chen +1
Evaluation metrics are crucial in the field of code synthesis. Commonly used code evaluation metrics canbe classified into three types: match-based, semantic-based, and execution-b…
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…
Assessing and Improving Syntactic Adversarial Robustness of Pre-trained Models for Code Translation
Guang Yang, Yu Zhou, Xiangyu Zhang +3
Context: Pre-trained models (PTMs) have demonstrated significant potential in automatic code translation. However, the vulnerability of these models in translation tasks, particula…