59 citations · 104 across the 9 of their papers we have counts for
9 papers
AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me
Minju Park, Seunghyun Lee, Juhwan Ma +1
Advances in AI have enabled ESL learners to practice speaking through conversational systems. However, most tools rely on explicit correction, which can interrupt the conversation…
BIPED: Pedagogically Informed Tutoring System for ESL Education
Soonwoo Kwon, Sojung Kim, Minju Park +2
Large Language Models (LLMs) have a great potential to serve as readily available and cost-efficient Conversational Intelligent Tutoring Systems (CITS) for teaching L2 learners of…
Empowering Personalized Learning through a Conversation-based Tutoring System with Student Modeling
Minju Park, Sojung Kim, Seunghyun Lee +2
As the recent Large Language Models(LLM's) become increasingly competent in zero-shot and few-shot reasoning across various domains, educators are showing a growing interest in lev…
Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach
Soonwoo Kwon, Sojung Kim, Seunghyun Lee +3
Computerized Adaptive Testing (CAT) is a widely used, efficient test mode that adapts to the examinee's proficiency level in the test domain. CAT requires pre-trained item profiles…
Addressing Negative Transfer in Diffusion Models
Hyojun Go, JinYoung Kim, Yunsung Lee +4
Diffusion-based generative models have achieved remarkable success in various domains. It trains a shared model on denoising tasks that encompass different noise levels simultaneou…
Towards Practical Plug-and-Play Diffusion Models
Hyojun Go, Yunsung Lee, Jin-Young Kim +4
Diffusion-based generative models have achieved remarkable success in image generation. Their guidance formulation allows an external model to plug-and-play control the generation…
Evaluating the Knowledge Dependency of Questions
Hyeongdon Moon, Yoonseok Yang, Jamin Shin +6
The automatic generation of Multiple Choice Questions (MCQ) has the potential to reduce the time educators spend on student assessment significantly. However, existing evaluation m…
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble
Seunghyun Lee, Younggyo Seo, Kimin Lee +2
Recent advance in deep offline reinforcement learning (RL) has made it possible to train strong robotic agents from offline datasets. However, depending on the quality of the train…
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
Kimin Lee, Younggyo Seo, Seunghyun Lee +2
Model-based reinforcement learning (RL) enjoys several benefits, such as data-efficiency and planning, by learning a model of the environment's dynamics. However, learning a global…