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20242026
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cs.CL2026

Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization

Jaewook Lee, Alexander Scarlatos, Simon Woodhead +1

With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become increasingly prominent. Prior wo…

cs.CL2026

Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues

Zhangqi Duan, Shuyan Huang, Alexander Scarlatos +3

A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor m…

cs.CL2026

Simulated Students in Tutoring Dialogues: Substance or Illusion?

Alexander Scarlatos, Jaewook Lee, Simon Woodhead +1

Advances in large language models (LLMs) enable many new innovations in education. However, evaluating the effectiveness of new technology requires real students, which is time-con…

cs.CL2026

Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues

Shuyan Huang, Alexander Scarlatos, Jaewook Lee +1

Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue. To enable these tutoring s…

cs.CL2025

PhoniTale: Phonologically Grounded Mnemonic Generation for Typologically Distant Language Pairs

Sana Kang, Myeongseok Gwon, Su Young Kwon +4

Vocabulary acquisition poses a significant challenge for second-language (L2) learners, especially when learning typologically distant languages such as English and Korean, where p…

cs.CL2025

SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction

Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod +2

Item (question) difficulties play a crucial role in educational assessments, enabling accurate and efficient assessment of student abilities and personalization to maximize learnin…