mlsanityData to 14 Oct 2026

KNIMEZoBot: Enhancing Literature Review with Zotero and KNIME OpenAI Integration using Retrieval-Augmented Generation

arXiv 2311.04310 ↗First posted 7 Nov 2023cs.HCcited by 2

On the map: Retrieval-augmented generation → Agentic RAG, agents and memory

Abstract (arXiv)

Academic researchers face challenges keeping up with exponentially growing published findings in their field. Performing comprehensive literature reviews to synthesize knowledge is time-consuming and labor-intensive using manual approaches. Recent advances in artificial intelligence provide promising solutions, yet many require coding expertise, limiting accessibility. KNIMEZoBot represents an innovative integration of Zotero, OpenAI, and the KNIME visual programming platform to automate literature review tasks for users with no coding experience. By leveraging KNIME's intuitive graphical interface, researchers can create workflows to search their Zotero libraries and utilize OpenAI models to extract key information without coding. Users simply provide API keys and configure settings through a user-friendly interface in a locally stored copy of the workflow. KNIMEZoBot then allows asking natural language questions via a chatbot and retrieves relevant passages from papers to generate synthesized answers. This system has significant potential to expedite literature reviews for researchers unfamiliar with coding by automating retrieval and analysis of publications in personal Zotero libraries. KNIMEZoBot demonstrates how thoughtfully designed AI tools can expand accessibility and accelerate knowledge building across diverse research domains.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation. Builds on 3 of its 26 references that are in the map. First posted on arXiv 7 Nov 2023.

Builds on

3 of 26 references.

References · 3

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023Benchmarking Large Language Models in Retrieval-Augmented Generationcited by 312
  3. 2020Growth rates of modern science: A latent piecewise growth curve approach to model publication numbers from established and new literature databasescited by 75

Built on by

Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024PyZoBot: A Platform for Conversational Information Extraction and Synthesis from Curated Zotero Reference Libraries through Advanced Retrieval-Augmented Generationcited by 0
  2. 2024A Retrieval-Augmented Generation Framework for Academic Literature Navigation in Data Sciencecited by 0

Similar, not cited

Close in wording, no citation either way

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  2. 2026Enhancing Scientific Literature Chatbots with Retrieval-Augmented Generation: A Performance Evaluation of Vector and Graph-Based Systems
  3. 2024System for systematic literature review using multiple AI agents: Concept and an empirical evaluation
  4. 2024OpenResearcher: Unleashing AI for Accelerated Scientific Research
  5. 2025AISSISTANT: Human-AI Collaborative Review and Perspective Research Workflows in Data Science
  6. 2023GEAR-Up: Generative AI and External Knowledge-based Retrieval Upgrading Scholarly Article Searches for Systematic Reviews
  7. 2025The Budget AI Researcher and the Power of RAG Chains
  8. 2025WisPaper: Your AI Scholar Search Engine