arXiv Machine Learning September 11, 2026 By Peiyuan Gao, Gaoyuan Zhang, Haojie Qin, Yahui Sun, Qianyi Zhang, Yunhao Zhang, Zeyu Wang, Wei Lu

VikingRAG: Accurate and Token-efficient Retrieval-augmented Generation over Structured Documents

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VikingRAG is a directory‑aware semantic data management system that reduces token usage in retrieval‑augmented generation by tightly integrating semantic and structural access. It employs multi‑round retrieval traces as reusable experience edges and an adaptive escalation strategy to avoid unnecessary multi‑round exploration. Experiments show that VikingRAG achieves comparable accuracy to state‑of‑the‑art methods while using only 11.6%–51.9% of their tokens, and further reductions to 5.1%–32.5% with trace reuse and escalation.

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arXiv Computation and Language

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ICICLE: Expanding Retrieval with In-Context Documents

M-RAG: Semantic Key-Value Indexing for Retrieval-Augmented Generation

A2RAG: Adaptive Agentic Graph Retrieval for Cost-Aware and Reliable Reasoning

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