6 papers
CatchAll: Repository-Aware Exception Handling with Knowledge-Guided LLMs
Qingxiao Tao, Xiaodong Gu, Hao Zhong +1
Exception handling is a vital forward error-recovery mechanism in many programming languages, enabling developers to manage runtime anomalies through structured constructs (e.g., t…
Beyond Language Boundaries: Uncovering Programming Language Families for Code Language Models
Shangbo Yun, Xiaodong Gu, Jianghong Huang +1
The rapid proliferation of diverse programming languages presents both opportunities and challenges for developing multilingual code LLMs. While existing techniques often train cod…
Transplant Then Regenerate: A New Paradigm for Text Data Augmentation
Guangzhan Wang, Hongyu Zhang, Beijun Shen +1
Data augmentation is a critical technique in deep learning. Traditional methods like Back-translation typically focus on lexical-level rephrasing, which primarily produces variatio…
Anti-adversarial Learning: Desensitizing Prompts for Large Language Models
Xuan Li, Zhe Yin, Xiaodong Gu +1
With the widespread use of LLMs, preserving privacy in user prompts has become crucial, as prompts risk exposing privacy and sensitive data to the cloud LLMs. Traditional technique…
Empowering AI to Generate Better AI Code: Guided Generation of Deep Learning Projects with LLMs
Chen Xie, Mingsheng Jiao, Xiaodong Gu +1
While large language models (LLMs) have been widely applied to code generation, they struggle with generating entire deep learning projects, which are characterized by complex stru…
APIRAT: Integrating Multi-source API Knowledge for Enhanced Code Translation with LLMs
Chaofan Wang, Guanjie Qiu, Xiaodong Gu +1
Code translation is an essential task in software migration, multilingual development, and system refactoring. Recent advancements in large language models (LLMs) have demonstrated…