PonsRAG: A Pons-Inspired RAG Bridging Cognitive Islands for Coordinated Long Narrative Reasoning

2026-08-26

AI Summary

为解决长叙事推理中的认知孤岛与跨层证据断连问题，提出PonsRAG框架，通过三层索引和协调推理方法，实现信息的连接与整合。

Abstract

Long Narrative Reasoning is an essential capability for processing and reasoning over complex narratives. While retrieval-augmented generation provides a promising framework, existing methods still face two critical challenges: cognitive islanding and cross-layer evidence disconnection. To address these issues, we propose PonsRAG, a coordinated RAG framework inspired by the biological pons. PonsRAG consists of two key components: Triple-Layer Indexing, which organizes documents into a connected knowledge structure to bridge cognitive islands, and Coordinated Reasoning, which retrieves evidence across distinct layers and integrates cross-layer information into a unified context. We evaluate PonsRAG on four long-context narrative benchmarks, and experimental results show that it outperforms the strongest baseline, achieving a 11.56% relative improvement in average accuracy on multi-choice tasks.

Problem

• Long Narrative Reasoning
• cognitive islanding
• cross-layer evidence disconnection

Innovation

• Triple-Layer Indexing
• Coordinated Reasoning
• Cognitive Islands
• Cross-layer Evidence Disconnection
• Long Narrative Reasoning