3 papers
cs.SE2025
CoCoEvo: Co-Evolution of Programs and Test Cases to Enhance Code Generation
Kefan Li, Yuan Yuan, Hongyue Yu +2
Large Language Models (LLMs) have shown remarkable performance in automated code generation. However, existing approaches often rely heavily on pre-defined test cases, which become…
cs.LG2024
CRTRE: Causal Rule Generation with Target Trial Emulation Framework
Junda Wang, Weijian Li, Han Wang +5
Causal inference and model interpretability are gaining increasing attention, particularly in the biomedical domain. Despite recent advance, decorrelating features in nonlinear env…
cs.CR2024
Data Extraction Attacks in Retrieval-Augmented Generation via Backdoors
Yuefeng Peng, Junda Wang, Hong Yu +1
Despite significant advancements, large language models (LLMs) still struggle with providing accurate answers when lacking domain-specific or up-to-date knowledge. Retrieval-Augmen…