mlsanityData to 14 Oct 2026

TrueReason: An Exemplar Personalised Learning System Integrating Reasoning with Foundational Models

arXiv 2502.10411 ↗First posted 23 Jan 2025cs.CY cs.AI cs.CLcited by 2

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Personalised education is one of the domains that can greatly benefit from the most recent advances in Artificial Intelligence (AI) and Large Language Models (LLM). However, it is also one of the most challenging applications due to the cognitive complexity of teaching effectively while personalising the learning experience to suit independent learners. We hypothesise that one promising approach to excelling in such demanding use cases is using a society of minds. In this chapter, we present TrueReason, an exemplar personalised learning system that integrates a multitude of specialised AI models that can mimic micro skills that are composed together by a LLM to operationalise planning and reasoning. The architecture of the initial prototype is presented while describing two micro skills that have been incorporated in the prototype. The proposed system demonstrates the first step in building sophisticated AI systems that can take up very complex cognitive tasks that are demanded by domains such as education.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 27 of its 72 references that are in the map. First posted on arXiv 23 Jan 2025.

Builds on

27 of 72 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023ARN: Analogical Reasoning on Narratives2 Oct

Other references · 26

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
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14 more
  1. 2024Tool Learning in the Wild: Empowering Language Models as Automatic Tool Agentscited by 56
  2. 2024Learning to Use Tools via Cooperative and Interactive Agentscited by 54
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  6. 2024How Teachers Can Use Large Language Models and Bloom's Taxonomy to Create Educational Quizzescited by 17
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  14. 2022Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experimentscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025A Human-Centric Approach to Explainable AI for Personalized Education
  2. 2025Bridging LLMs and Symbolic Reasoning in Educational QA Systems: Insights from the XAI Challenge at IJCNN 2025
  3. 2025A Theory of Adaptive Scaffolding for LLM-Based Pedagogical Agents
  4. 2025Toward Generalized Autonomous Agents: A Neuro-Symbolic AI Framework for Integrating Social and Technical Support in Education
  5. 2026Modularizing Educational LLM-Agency for Fostering Responsible Learning Assistance
  6. 2025ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems
  7. 2025Human-Level Reasoning: A Comparative Study of Large Language Models on Logical and Abstract Reasoning
  8. 2025Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI