1 citations · 3 across the 7 of their papers we have counts for
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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…
PreMix: Label-Efficient Multiple Instance Learning via Non-Contrastive Pre-training and Feature Mixing
Bryan Wong, Mun Yong Yi
Multiple instance learning (MIL) has emerged as a powerful framework for weakly supervised whole slide image (WSI) classification, enabling slide-level predictions without requirin…
Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning
Jongwoo Kim, Seongyeub Chu, Hyeongmin Park +3
Recent advancements in graph neural networks (GNNs) and heterogeneous GNNs (HGNNs) have advanced node embeddings and relationship learning for various tasks. However, existing meth…