4 papers
REC-CBM: Rubric-Aware Error-Correction Concept Bottleneck Models for Trustworthy Open-Ended Grading
Chengshuai Zhao, Fan Zhang, Kumar Satvik Chaudhary +4
Open-ended grading is central to equitable and personalized education, yet manual grading remains time-consuming and costly, underscoring the need for automated grading systems. Al…
EssayCBM: Rubric-Aligned Concept Bottleneck Models for Transparent Essay Grading
Kumar Satvik Chaudhary, Chengshuai Zhao, Fan Zhang +3
Automated essay scoring (AES) has advanced significantly with neural language models, yet most systems remain opaque, offering little visibility into how grades are produced. In ed…
CyberBOT: Towards Reliable Cybersecurity Education via Ontology-Grounded Retrieval Augmented Generation
Chengshuai Zhao, Riccardo De Maria, Tharindu Kumarage +7
Advancements in large language models (LLMs) have enabled the development of intelligent educational tools that support inquiry-based learning across technical domains. In cybersec…
SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Dawei Li, Zhen Tan, Peijia Qian +4
While multi-agent systems have been shown to significantly enhance the performance of Large Language Models (LLMs) across various tasks and applications, the dense interaction betw…