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Sung-Hyun Maeng

Korea Advanced Institute of Science and Technology

About the Lab

Professor Sung-Hyun Maeng's research lab specializes in artificial intelligence, with a focus on question answering systems, multi-agent reasoning, and adaptive learning strategies. The lab develops intelligent, modular QA architectures that dynamically select and coordinate multiple reasoning modules based on learned strategies to improve accuracy and efficiency. Their work emphasizes strategy learning and confidence-based decision making to enhance system robustness and scalability. The lab also explores applications in human-AI collaboration and explainable AI through modular, interpretable reasoning frameworks.

question answeringstrategy learningmodular reasoningconfidence calibrationAI systems

Research Overview

Papers
1
Total Citations
6
Papers (5y)
1
Primary Field

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
1total
2009
Citations per year (5y)
6total
2009

Selected Papers

1
1
Article|6 citations·2009
Enhancing Performance with a Learnable Strategy for Multiple Question Answering Modules
Hyo-Jung Oh, Myung-Gil Jang, 맹성현

A question answering (QA) system can be built using multiple QA modules that can individually serve as a QA system in and of themselves. This paper proposes a learnable, strategy-driven QA model that aims at enhancing both efficiency and effectiveness. A strategy is learned using a learning-based classification algorithm that determines the sequence of QA modules to be invoked and decides when to stop invoking additional modules. The learned strategy invokes the most suitable QA module for a giv

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