mlsanityData to 7 Oct 2026

Cross-Data Knowledge Graph Construction for LLM-enabled Educational Question-Answering System: A Case Study at HCMUT

arXiv 2404.09296 ↗First posted 14 Apr 2024cs.CLcited by 14

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Abstract (arXiv)

In today's rapidly evolving landscape of Artificial Intelligence, large language models (LLMs) have emerged as a vibrant research topic. LLMs find applications in various fields and contribute significantly. Despite their powerful language capabilities, similar to pre-trained language models (PLMs), LLMs still face challenges in remembering events, incorporating new information, and addressing domain-specific issues or hallucinations. To overcome these limitations, researchers have proposed Retrieval-Augmented Generation (RAG) techniques, some others have proposed the integration of LLMs with Knowledge Graphs (KGs) to provide factual context, thereby improving performance and delivering more accurate feedback to user queries. Education plays a crucial role in human development and progress. With the technology transformation, traditional education is being replaced by digital or blended education. Therefore, educational data in the digital environment is increasing day by day. Data in higher education institutions are diverse, comprising various sources such as unstructured/structured text, relational databases, web/app-based API access, etc. Constructing a Knowledge Graph from these cross-data sources is not a simple task. This article proposes a method for automatically constructing a Knowledge Graph from multiple data sources and discusses some initial applications (experimental trials) of KG in conjunction with LLMs for question-answering tasks.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 16 of its 32 references that are in the map. First posted on arXiv 14 Apr 2024.

Builds on

16 of 32 references.

References · 16

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  2. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  4. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
  5. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  6. 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,414
  7. 2020Knowledge Graphscited by 619
  8. 2020Efficient Intent Detection with Dual Sentence Encoderscited by 419
  9. 2020MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformerscited by 240
  10. 2020PhoBERT: Pre-trained language models for Vietnamesecited by 148
  11. 2023Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answeringcited by 119
  12. 2023The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuningcited by 106
4 more
  1. 2023Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generationcited by 54
  2. 2019Towards Open Intent Discovery for Conversational Textcited by 13
  3. 2021PhoNLP: A joint multi-task learning model for Vietnamese part-of-speech tagging, named entity recognition and dependency parsingcited by 13
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 3.

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  1. 2024Multi-Head RAG: Solving Multi-Aspect Problems with LLMscited by 18
  2. 2025Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applicationscited by 6
  3. 2025URAG: Implementing a Unified Hybrid RAG for Precise Answers in University Admission Chatbots -- A Case Study at HCMUTcited by 2
  4. 2025Jingfang: An LLM-Based Multi-Agent System for Precise Medical Consultation and Syndrome Differentiation in Traditional Chinese Medicinecited by 2
  5. 2025KAQG: A Knowledge-Graph-Enhanced RAG for Difficulty-Controlled Question Generationcited by 2
  6. 2025An Empirical Study of Multi-Agent RAG for Real-World University Admissions Counselingcited by 2
  7. 2025AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Datacited by 2
  8. 2024ERATTA: Extreme RAG for Table To Answers with Large Language Modelscited by 1
  9. 2024Transformative Influence of LLM and AI Tools in Student Social Media Engagement: Analyzing Personalization, Communication Efficiency, and Collaborative Learningcited by 1
  10. 2025Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approachcited by 1
  11. 2026Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrievalcited by 1
  12. 2025Handling Students Dropouts in an LLM-driven Interactive Online Course Using Language Modelscited by 0
2 more
  1. 2026TCM-DiffRAG: Personalized Syndrome Differentiation Reasoning Method for Traditional Chinese Medicine based on Knowledge Graph and Chain of Thoughtcited by 0
  2. 2026A didactical-driven teacher assistant for a dimensional modeling coursecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Aligning LLMs for the Classroom with Knowledge-Based Retrieval -- A Comparative RAG Study
  2. 2025Knowledge Graph-extended Retrieval Augmented Generation for Question Answering
  3. 2024KnowShiftQA: How Robust are RAG Systems when Textbook Knowledge Shifts in K-12 Education?
  4. 2024KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation
  5. 2025Fusing Knowledge and Language: A Comparative Study of Knowledge Graph-Based Question Answering with LLMs
  6. 2025Answering Students' Questions on Course Forums Using Multiple Chain-of-Thought Reasoning and Finetuning RAG-Enabled LLM
  7. 2025Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey
  8. 2025Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generation