Enhancing Scientific Literature Chatbots with Retrieval-Augmented Generation: A Performance Evaluation of Vector and Graph-Based Systems
On the map: Retrieval-augmented generation → Agentic RAG, agents and memory
Abstract (arXiv)
This paper investigates the enhancement of scientific literature chatbots through retrieval-augmented generation (RAG), with a focus on evaluating vector- and graph-based retrieval systems. The proposed chatbot leverages both structured (graph) and unstructured (vector) databases to access scientific articles and gray literature, enabling efficient triage of sources according to research objectives. To systematically assess performance, we examine two use-case scenarios: retrieval from a single uploaded document and retrieval from a large-scale corpus. Benchmark test sets were generated using a GPT model, with selected outputs annotated for evaluation. The comparative analysis emphasizes retrieval accuracy and response relevance, providing insight into the strengths and limitations of each approach. The findings demonstrate the potential of hybrid RAG systems to improve accessibility to scientific knowledge and to support evidence-based decision making.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation. Builds on 9 of its 15 references that are in the map. First posted on arXiv 19 Feb 2026.
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9 of 15 references.
References · 9
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,221
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,196
- 2024Evaluation of Retrieval-Augmented Generation: A Surveycited by 146
- 2024LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMscited by 106
- 2024Evaluating Retrieval Quality in Retrieval-Augmented Generationcited by 90
- 2025PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Pathscited by 60
- 2024Socially Aware Synthetic Data Generation for Suicidal Ideation Detection Using Large Language Modelscited by 10
- 2024A review of faithfulness metrics for hallucination assessment in Large Language Modelscited by 9
- 2025TrustRAG: An Information Assistant with Retrieval Augmented Generationcited by 1
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- 2025A Knowledge Graph and a Tripartite Evaluation Framework Make Retrieval-Augmented Generation Scalable and Transparent
- 2025HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights
- 2025HybridRAG: A Practical LLM-based ChatBot Framework based on Pre-Generated Q&A over Raw Unstructured Documents
- 2025Chatting with Papers: A Hybrid Approach Using LLMs and Knowledge Graphs
- 2025A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems
- 2024From Questions to Insightful Answers: Building an Informed Chatbot for University Resources
- 2025A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot
- 2024A Retrieval-Augmented Generation Framework for Academic Literature Navigation in Data Science