SPD-RAG: Sub-Agent Per Document Retrieval-Augmented Generation

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References (16)

[1]
Towards a Science of Scaling Agent Systems
2025Y. Kim, Ken Gu et al.
[2]
LLM-empowered knowledge graph construction: A survey
2025Haonan Bian
[3]
MoNaCo: More Natural and Complex Questions for Reasoning Across Dozens of Documents
2025Tomer Wolfson, H. Trivedi et al.
[4]
MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding
2025Siwei Han, Peng Xia et al.
[5]
MEBench: Benchmarking Large Language Models for Cross-Document Multi-Entity Question Answering
2025Teng Lin
[6]
Context-Aware Hierarchical Merging for Long Document Summarization
2025Litu Ou, Mirella Lapata
[7]
AgentOrchestra: A Hierarchical Multi-Agent Framework for General-Purpose Task Solving
2025Wentao Zhang, Ce Cui et al.
[8]
DocAgent: An Agentic Framework for Multi-Modal Long-Context Document Understanding
2025Li Sun, Liu He et al.
[9]
Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data
2024Seiji Maekawa, Hayate Iso et al.
[10]
MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs
2024Qian Wang, Tianyu Wang et al.
[11]
Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA
2024Minzheng Wang, Longze Chen et al.
[12]
From Local to Global: A Graph RAG Approach to Query-Focused Summarization
2024Darren Edge, Ha Trinh et al.
[13]
Lost in the Middle: How Language Models Use Long Contexts
2023Nelson F. Liu, Kevin Lin et al.
[14]
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
2020Patrick Lewis, Ethan Perez et al.
[15]
Synthesizer
2019Sloan Kate
[16]
From Louvain to Leiden: guaranteeing well-connected communities
2018V. Traag, L. Waltman et al.

Founder's Pitch

"SPD-RAG is a hierarchical multi-agent framework for question answering that decomposes the problem along the document axis, improving scalability and answer quality."

RAGScore: 7View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

2/4 signals

5

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4/4 signals

10

Series A Potential

2/4 signals

5

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