Tag
This paper introduces Shapley Context Pruning (SCP), a cooperative game-theoretic framework for context reranking and pruning in RAG systems. It employs a Deep Sets architecture and Monte-Carlo sampling to efficiently attribute importance to sentences, achieving competitive downstream QA performance with a lightweight 3M-parameter value network.