mlsanityData to 14 Oct 2026

Multimodality of AI for Education: Towards Artificial General Intelligence

arXiv 2312.06037 ↗First posted 10 Dec 2023cs.AIcited by 21

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Abstract (arXiv)

This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intelligence (AGI) in educational contexts. It scrutinizes the evolution and integration of AI in educational systems, emphasizing the crucial role of multimodality, which encompasses auditory, visual, kinesthetic, and linguistic modes of learning. This research delves deeply into the key facets of AGI, including cognitive frameworks, advanced knowledge representation, adaptive learning mechanisms, strategic planning, sophisticated language processing, and the integration of diverse multimodal data sources. It critically assesses AGI's transformative potential in reshaping educational paradigms, focusing on enhancing teaching and learning effectiveness, filling gaps in existing methodologies, and addressing ethical considerations and responsible usage of AGI in educational settings. The paper also discusses the implications of multimodal AI's role in education, offering insights into future directions and challenges in AGI development. This exploration aims to provide a nuanced understanding of the intersection between AI, multimodality, and education, setting a foundation for future research and development in AGI.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 62 of its 252 references that are in the map. First posted on arXiv 10 Dec 2023.

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62 of 252 references.

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Citing papers per year: 2023: 1; 2024: 13; 2025: 6; 2026: 1.

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  1. 2024Revolutionizing Finance with LLMs: An Overview of Applications and Insightscited by 90
  2. 2024Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Researchcited by 27
  3. 2024Large Language Models for Manufacturingcited by 24
  4. 2023From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscapecited by 18
  5. 2024A Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Educationcited by 16
  6. 2024Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Educationcited by 15
  7. 2025Aligning Multimodal Representations through an Information Bottleneckcited by 13
  8. 2024Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translationcited by 12
  9. 2024GP-GPT: Large Language Model for Gene-Phenotype Mappingcited by 11
  10. 2025EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Modelscited by 7
  11. 2024Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reportscited by 6
  12. 2025Towards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocolscited by 6
9 more
  1. 2024Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AIcited by 5
  2. 2024Foundation Models for Low-Resource Language Education (Vision Paper)cited by 5
  3. 2024Legal Evalutions and Challenges of Large Language Modelscited by 4
  4. 2025Large Language Models for Bioinformaticscited by 3
  5. 2025Multimodal Representation Learning and Fusioncited by 3
  6. 2024G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in Germancited by 2
  7. 2024Evaluating the Usability of LLMs in Threat Intelligence Enrichmentcited by 2
  8. 2025EduPersona: Benchmarking Subjective Ability Boundaries of Virtual Student Agentscited by 0
  9. 2026Chart Deep Research in LVLMs via Parallel Relative Policy Optimizationcited by 0