Investigating Flavors of RAG for Applications in College Chatbots

Christian Sarmiento; Eitel Lauría

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Investigating Flavors of RAG for Applications in College Chatbots

Topics: Architectures for AI-based Educational Systems; Intelligent Learning and Teaching Systems; Natural Language Processing

In Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU, 421-428, 2025 , Porto, Portugal

Authors: Christian Sarmiento and Eitel Lauría

Affiliation: School of Computer Science and Mathematics, Marist University, Poughkeepsie, NY 12601, U.S.A.

Keyword(s): Retrieval Augmented Generation, Machine Learning, Large Language Models, AI, NLP, Higher Education.

Abstract: Retrieval Augmented Generation (RAG) has become a growing area of interest in machine learning (ML) and large language models (LLM) for its ability to improve reasoning by grounding responses in relevant contexts. This study analyzes two RAG architectures, RAG’s original design and Corrective RAG. Through a detailed examination of these architectures, their components, and performance, this work underscores the need for robust metrics when assessing RAG architectures and highlights the importance of good quality context documents in building systems that can mitigate LLM limitations, providing valuable insight for academic institutions to design efficient and accurate question-answering systems tailored to institutional needs.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 216.73.216.157

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Sarmiento, C., Lauría and E. (2025). Investigating Flavors of RAG for Applications in College Chatbots. In Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU; ISBN 978-989-758-746-7; ISSN 2184-5026, SciTePress, pages 421-428. DOI: 10.5220/0013468200003932

@conference{csedu25,
author={Christian Sarmiento and Eitel Lauría},
title={Investigating Flavors of RAG for Applications in College Chatbots},
booktitle={Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU},
year={2025},
pages={421-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013468200003932},
isbn={978-989-758-746-7},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Computer Supported Education - Volume 2: CSEDU
TI - Investigating Flavors of RAG for Applications in College Chatbots
SN - 978-989-758-746-7
IS - 2184-5026
AU - Sarmiento, C.
AU - Lauría, E.
PY - 2025
SP - 421
EP - 428
DO - 10.5220/0013468200003932
PB - SciTePress