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Can Multimodal Large Language Models Grade Like an Expert? A Study on UML Class Diagram Assessment Accuracy
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Proceedings of the 16th annual joint conference on Innovation and technology in computer science education
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-36590-3_22openalex-snapshot
Assessment of SOLID Principles in UML Class Diagrams Using LLMs
inferred← citeshttps://doi.org/10.1007/978-3-032-38498-0_24openalex-snapshot
Evaluating LLM-Generated Conceptual Models: A Theoretical Approach for Formalizing the Calculation of Metrics on the Meta Level
inferred← citeshttps://doi.org/10.1007/s10270-026-01427-0openalex-snapshot
Generating UML class diagrams as conceptual models through large language models
inferred← citeshttps://doi.org/10.1016/j.ssaho.2026.103144openalex-snapshot
A comparative analytical study of LLM-based automated grading in programming education
inferred← citeshttps://doi.org/10.1080/17517575.2026.2629556openalex-snapshot
Performance of multimodal large language model in understanding digital UML class diagram
inferred← citeshttps://doi.org/10.1109/rew72749.2026.00060openalex-snapshot
Towards Satisfaction Analysis of GRL Model Images Using Vision-Enabled LLMS
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inferred← citeshttps://doi.org/10.1145/3837062.3838917openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3837062.3839375openalex-snapshot
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inferred← citeshttps://doi.org/10.21203/rs.3.rs-8985839/v1openalex-snapshot
Architectural Transparency in LLM-Based Cognitive Assessment: A Multidimensional TRACE-ED Evaluation of Single-Agent and Multi-Agent Systems
inferred← citeshttps://doi.org/10.3390/educsci16010123openalex-snapshot
Vision-Language Models in Teaching and Learning: A Systematic Literature Review
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