# Chatting with Papers: A Hybrid Approach Using LLMs and Knowledge Graphs

arXiv: https://arxiv.org/abs/2505.11633 · HTML: https://mlsanity.com/paper/2505.11633/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 20 references that are in the map.
- First posted on arXiv 16 May 2025.

## Builds on (most cited first, 9 of 9)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [From Local to Global: A Graph RAG Approach to Query-Focused Summarization](https://mlsanity.com/paper/2404.16130/) (2024)
- [A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://mlsanity.com/paper/2405.06211/) (2024)
- [LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples](https://mlsanity.com/paper/2310.01469/) (2023)
- [Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review](https://mlsanity.com/paper/1801.04479/) (2018)
- [A Knowledge Base for Arts and Inclusion -- The Dataverse data archival platform as a knowledge base management system enabling multimodal accessibility](https://mlsanity.com/paper/2504.05976/) (2025)
- [Scientometrics and Information Retrieval - weak-links revitalized](https://mlsanity.com/paper/1411.1635/) (2014)
- [A maturity model for catalogues of semantic artefacts](https://mlsanity.com/paper/2305.06746/) (2023)
- [Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study](https://mlsanity.com/paper/2408.13501/) (2024)

## Built on by (most cited first, 1 of 1)

- [Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives](https://mlsanity.com/paper/2506.12242/) (2025)

## Abstract (arXiv)

This demo paper reports on a new workflow textitGhostWriter that combines the use of Large Language Models and Knowledge Graphs (semantic artifacts) to support navigation through collections. Situated in the research area of Retrieval Augmented Generation, this specific workflow represents the creation of local and adaptable chatbots. Based on the tool-suite textitEverythingData at the backend, textitGhostWriter provides an interface that enables querying and ``chatting'' with a collection. Applied iteratively, the workflow supports the information needs of researchers when interacting with a collection of papers, whether it be to gain an overview, to learn more about a specific concept and its context, and helps the researcher ultimately to refine their research question in a controlled way. We demonstrate the workflow for a collection of articles from the textitmethod data analysis journal published by GESIS -- Leibniz-Institute for the Social Sciences. We also point to further application areas.