2 papers
cs.CL2026
DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation
Rui Chu, Bingyin Zhao, Thanh Quoc Hung Le +6
Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on knowledge encapsulated from train…
cs.DC2025
GPU Kernel Optimization Beyond Full Builds: An LLM Framework with Minimal Executable Programs
Ruifan Chu, Anbang Wang, Xiuxiu Bai +2
In high-performance computing, hotspot GPU kernels are primary bottlenecks, and expert manual tuning is costly and hard to port. Large language model methods often assume kernels c…