most citedOffsetBias: Leveraging Debiased Data for Tuning Evaluators

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Detecting Knowledge Gaps from Conversational AI Interactions Using Curriculum Prerequisite Graphs

Youssef Medhat, Junsoo Park, Ploy Thajchayapong +1

Large online courses generate thousands of student questions directed at conversational AI teaching assistants, yet these interaction logs remain largely untapped as diagnostic sig…

cs.AI2026

Surfacing Isolated Learners with Outcome-Independent Mediation of Feedback between Teachers and Students Using AI

Junsoo Park, Youssef Medhat, Htet Phyo Wai +2

AI-augmented classrooms generate rich teacher and student feedback before graded outcomes become available, yet these signals can be difficult to translate into timely instructiona…

cs.IR2026

Memory-Based vs. Context-Only Conditioning Produces Distinct Behavioral Patterns in Stateful Personalization

Junsoo Park, Youssef Medhat, Htet Phyo Wai +2

We study how conditioning context shapes personalization behavior in a teacher-facing educational recommender system. We compare contextual conditioning based on the current studen…

cs.CL2026

Evaluating Learner Representations for Differentiation Prior to Instructional Outcomes

Junsoo Park, Youssef Medhat, Htet Phyo Wai +2

Learner representations play a central role in educational AI systems, yet it is often unclear whether they preserve meaningful differences between students when instructional outc…

cs.CL2024★ 1 cited

OffsetBias: Leveraging Debiased Data for Tuning Evaluators

Junsoo Park, Seungyeon Jwa, Meiying Ren +2

Employing Large Language Models (LLMs) to assess the quality of generated responses, such as prompting instruct-tuned models or fine-tuning judge models, has become a widely adopte…