4 papers
A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations
Zihan Liu, Yizhen Wang, Rui Wang +2
Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource-constrained organizations. Wh…
Detecting Logic Bugs of Join Optimizations in DBMS
Xiu Tang, Sai Wu, Dongxiang Zhang +2
Generation-based testing techniques have shown their effectiveness in detecting logic bugs of DBMS, which are often caused by improper implementation of query optimizers. Nonethele…
Learner-Tailored Program Repair: A Solution Generator with Iterative Edit-Driven Retrieval Enhancement
Zhenlong Dai, Zhuoluo Zhao, Hengning Wang +5
With the development of large language models (LLMs) in the field of programming, intelligent programming coaching systems have gained widespread attention. However, most research…
MorphingDB: A Task-Centric AI-Native DBMS for Model Management and Inference
Wu Sai, Xia Ruichen, Yang Dingyu +9
The increasing demand for deep neural inference within database environments has driven the emergence of AI-native DBMSs. However, existing solutions either rely on model-centric d…