ResearchResearch paperRetrieval, RAG & Search1 source · Oct 20, 2026

InsightRAG: Aggregating Distributed Scholarly Judgments for Scientific Survey Generation

The rapid growth of scientific literature makes survey writing increasingly challenging, motivating automatic survey generation.

Yet, existing systems must search an open space of papers and an open space of concepts with no trace of how the community itself has navigated them, leading to incomplete scope, weak taxonomies, and unreliable citations.
Our core insight is that author-written Related Work sections contain the human judgments needed to address both limitations: authors curate the citations relevant to their contributions and explain how the cited works relate, yielding paths for scope reconstruction and relational evidence for organization.
Its insight-guided retrieval follows author-supported citation relations to reconstruct a verified research scope and structure the resulting relational evidence.
Results on ten topics show gains in scope reconstruction, taxonomy quality, citation support, and reference reliability.

[1]InsightRAG: Aggregating Distributed Scholarly Judgments for Scientific Survey Generation
arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 20, 12:04 PM
The rapid growth of scientific literature makes survey writing increasingly challenging, motivating automatic survey generation.
Yet, existing systems must search an open space of papers and an open space of concepts with no trace of how the community itself has navigated them, leading to incomplete scope, weak taxonomies, and unreliable citations.

Extractive summary: sentences quoted from the sources.

Before this