Preprint
SymbioticRAG: Enhancing Document Intelligence Through Human-LLM Symbiotic Collaboration
ArXiv.org
Cornell University
2025
Abstract
We present SymbioticRAG, a novel framework that fundamentally reimagines Retrieval-Augmented Generation~(RAG) systems by establishing a bidirectional learning relationship between humans and machines. Our approach addresses two critical challenges in current RAG systems: the inherently human-centered nature of relevance determination and users' progression from "unconscious incompetence" in query formulation. SymbioticRAG introduces a two-tier solution where Level 1 enables direct human curation of retrieved content through interactive source document exploration, while Level 2 aims to build personalized retrieval models based on captured user interactions. We implement Level 1 through three key components: (1)~a comprehensive document processing pipeline with specialized models for layout detection, OCR, and extraction of tables, formulas, and figures; (2)~an extensible retriever module supporting multiple retrieval strategies; and (3)~an interactive interface that facilitates both user engagement and interaction data logging. We experiment Level 2 implementation via a retriever strategy incorporated LLM summarized user intention from user interaction logs. To maintain high-quality data preparation, we develop a human-on-the-loop validation interface that improves pipeline output while advancing research in specialized extraction tasks. Evaluation across three scenarios (literature review, geological exploration, and education) demonstrates significant improvements in retrieval relevance and user satisfaction compared to traditional RAG approaches. To facilitate broader research and further advancement of SymbioticRAG Level 2 implementation, we will make our system openly accessible to the research community.
Details
- Title
- SymbioticRAG: Enhancing Document Intelligence Through Human-LLM Symbiotic Collaboration
- Authors/Creators
- Qiang Sun - The University of Western AustraliaTingting Bi - The University of MelbourneSirui Li (Author) - Murdoch University, School of Information TechnologyEun-Jung HoldenPaul DuuringKai NiuWei Liu - Kunming Institute of Botany
- Publication Details
- ArXiv.org
- Publisher
- Cornell University
- Identifiers
- 991005824450307891
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Preprint
Metrics
25 File views/ downloads
6 Record Views