8 papers
SCRIBE: Structured Chain Reasoning for Interactive Behaviour Explanations using Tool Calling
Fares Fawzi, Vinitra Swamy, Dominik Glandorf +2
Language models can be used to provide interactive, personalized student feedback in educational settings. However, real-world deployment faces three key challenges: privacy concer…
Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems
Shang-Chi Tsai, Yun-Nung Chen
With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…
A Human-Centric Approach to Explainable AI for Personalized Education
Vinitra Swamy
Deep neural networks form the backbone of artificial intelligence research, with potential to transform the human experience in areas ranging from autonomous driving to personal as…
Intrinsic User-Centric Interpretability through Global Mixture of Experts
Vinitra Swamy, Syrielle Montariol, Julian Blackwell +3
In human-centric settings like education or healthcare, model accuracy and model explainability are key factors for user adoption. Towards these two goals, intrinsically interpreta…
iLLuMinaTE: An LLM-XAI Framework Leveraging Social Science Explanation Theories Towards Actionable Student Performance Feedback
Vinitra Swamy, Davide Romano, Bhargav Srinivasa Desikan +2
Recent advances in eXplainable AI (XAI) for education have highlighted a critical challenge: ensuring that explanations for state-of-the-art AI models are understandable for non-te…
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning
Elena Grazia Gado, Tommaso Martorella, Luca Zunino +4
Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primari…