Sizhong Cao

Bi-Level Preference Optimization for Retrieval-Augmented Generation (Student Abstract)

Retrieval-augmented generation (RAG) is the backbone of knowledge-intensive NLP, yet its progress is hindered by a long-standing asymmetry: Generators are refined while retrievers remain static, and full end-to-end optimization is prohibitively unstable. We present BPO-RAG, a bi-level preference-lea