Gilchan Park — accepted AI-conference papers

2025

Enhancing Future Link Prediction in Quantum Computing Semantic Networks through LLM-Initiated Node Features

Gilchan Park, Paul Baity, Byung-Jun Yoon, Adolfy Hoisie

COLING 2025industry

Quantum computing is rapidly evolving in both physics and computer science, offering the potential to solve complex problems and accelerate computational processes. The development of quantum chips necessitates understanding the correlations among diverse experimental conditions. Semantic networks b…

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2025

Pareto Prompt Optimization

Guang Zhao, Byung-Jun Yoon, Gilchan Park, Shantenu Jha, Shinjae Yoo, Xiaoning Qian

ICLR 2025poster

Natural language prompt optimization, or prompt engineering, has emerged as a powerful technique to unlock the potential of Large Language Models (LLMs) for various tasks. While existing methods primarily focus on maximizing a single task-specific performance metric for LLM outputs, real-world appli…

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