11 papers
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions
Luyang Fang, Xiaowei Yu, Jiazhang Cai +23
The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational and data demands. This survey p…
SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches
Ehsan Latif, Zirak Khan, Xiaoming Zhai
Scientific sketches (e.g., models) offer a powerful lens into students' conceptual understanding, yet AI-powered automated assessment of such free-form, visually diverse artifacts…
Efficient Multi-Task Inferencing with a Shared Backbone and Lightweight Task-Specific Adapters for Automatic Scoring
Ehsan Latif, Xiaoming Zhai
The integration of Artificial Intelligence (AI) in education requires scalable and efficient frameworks that balance performance, adaptability, and cost. This paper addresses these…
Artificial Intelligence Bias on English Language Learners in Automatic Scoring
Shuchen Guo, Yun Wang, Jichao Yu +7
This study investigated potential scoring biases and disparities toward English Language Learners (ELLs) when using automatic scoring systems for middle school students' written re…
Privacy-Preserved Automated Scoring using Federated Learning for Educational Research
Ehsan Latif, Xiaoming Zhai
Data privacy remains a critical concern in educational research, requiring strict adherence to ethical standards and regulatory protocols. While traditional approaches rely on anon…
Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment
Luyang Fang, Ehsan Latif, Haoran Lu +3
Automatic scoring of student responses enhances efficiency in education, but deploying a separate neural network for each task increases storage demands, maintenance efforts, and r…