2 papers
cs.LG2026
FedSDR: Federated Self-Distillation with Rectification
Ziheng Ren, Zhanming Shen, Hao Wang +2
Federated fine-tuning of Large Language Models faces severe statistical heterogeneity. However, existing model-level defenses often overlook the root cause: intrinsic data distribu…
cs.CL2026
Relevance to Utility: Process-Supervised Rewrite for RAG
Jaeyoung Kim, Jongho Kim, Seung-won Hwang +2
Retrieval-augmented generation systems often suffer from a gap between optimizing retrieval relevance and generative utility. With such a gap, retrieved documents may be topically…