1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
FeedEval: Pedagogically Aligned Evaluation of LLM-Generated Essay Feedback
Seongyeub Chu, Jongwoo Kim, Munyong Yi
Going beyond the prediction of numerical scores, recent research in automated essay scoring has increasingly emphasized the generation of high-quality feedback that provides justif…
Rationale Behind Essay Scores: Enhancing S-LLM's Multi-Trait Essay Scoring with Rationale Generated by LLMs
SeongYeub Chu, JongWoo Kim, Bryan Wong +1
Existing automated essay scoring (AES) has solely relied on essay text without using explanatory rationales for the scores, thereby forgoing an opportunity to capture the specific…
Not All Options Are Created Equal: Textual Option Weighting for Token-Efficient LLM-Based Knowledge Tracing
JongWoo Kim, SeongYeub Chu, Bryan Wong +1
Large Language Models (LLMs) have recently emerged as promising tools for knowledge tracing (KT) due to their strong reasoning and generalization abilities. While recent LLM-based…
Think Together and Work Better: Combining Humans' and LLMs' Think-Aloud Outcomes for Effective Text Evaluation
SeongYeub Chu, JongWoo Kim, MunYong Yi
This study introduces \textbf{InteractEval}, a framework that integrates human expertise and Large Language Models (LLMs) using the Think-Aloud (TA) method to generate attributes f…