Research Paper#AI in Education, Blockchain, Vision-Language Models🔬 ResearchAnalyzed: Jan 4, 2026 00:17
SlideChain: Verifiable Semantic Provenance for Educational Content
Published:Dec 25, 2025 14:02
•1 min read
•ArXiv
Analysis
This paper addresses the critical issue of trust and reproducibility in AI-generated educational content, particularly in STEM fields. It introduces SlideChain, a blockchain-based framework to ensure the integrity and auditability of semantic extractions from lecture slides. The work's significance lies in its practical approach to verifying the outputs of vision-language models (VLMs) and providing a mechanism for long-term auditability and reproducibility, which is crucial for high-stakes educational applications. The use of a curated dataset and the analysis of cross-model discrepancies highlight the challenges and the need for such a framework.
Key Takeaways
- •Introduces SlideChain, a blockchain-backed framework for verifiable semantic provenance in educational content.
- •Addresses the challenges of verifying, reproducing, and auditing AI-generated instructional material.
- •Demonstrates cross-model discrepancies in semantic extraction from lecture slides.
- •Provides a practical and scalable solution for trustworthy multimodal educational pipelines.
Reference
“The paper reveals pronounced cross-model discrepancies, including low concept overlap and near-zero agreement in relational triples on many slides.”