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Seung-Hwan Cho

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#artificial intelligence Preprint Sep 2026

Reasoning Externalization for Faithful Large Language Model Narratives of Stock Return Predictions

In finance, interpreting machine learning predictions is essential, yet the numerical outputs of explainable AI can be difficult for non-experts to understand. While large language models (LLMs) can translate these outputs into natural language, they may produce errors when inferring numerical changes and feature relat...

Sujung Kim, Seung-Hwan Cho, Sangjin Park et al. · 0 citations

#natural language process... Preprint Sep 2026

CARRE: Counterfactual Action Retrieval and Reason Evaluation for Explainable Churn Prescription

Retrieval ablations show that k=5 provides the best evaluated compromise between high candidate coverage and downstream reasoning agreement in this dataset, illustrating how retrieval, model-based counterfactual scoring, and language generation can be separated and jointly evaluated in a prototype churn-prescription pi...

Minjoo Kim, Sangjin Park, Seung-Hwan Cho · 0 citations

Jul 2026

MedJudgeRAG: Option-Wise Evidence Judgment with Dynamic Knowledge Graphs for Medical MCQA

Experiments on two medical MCQA benchmarks demonstrate that MedJudgeRAG consistently outperforms both vanilla RAG and parametric baselines, and ablation analysis reveals that the dynamic KG is more effective as graph-conditioned supervision at training time than as an explicit output at inference time.

Seongwon Seo, Seung-Hwan Cho, Young-Min Kim · arXiv.org · 0 citations