249 citations · 263 across the 17 of their papers we have counts for
21 papers
A Tutorial on Quantum Amplitude Embedding with Data Re-Uploading
Hyojun Ahn, Joongheon Kim
Amplitude embedding lets a variational quantum model read many classical features with few qubits, but the model output is then only a quadratic form in the normalized input. Data…
From LLM Plans to Authorized Motion: Execution-Bound Authorization for Excavators
Mehdi Heydari Shahna, Seihun Kim, Soyi Jung +3
An LLM-directed excavator can execute mechanically feasible motion whose destination or authority no longer matches the operator's approval. We propose execution-bound authorizatio…
IL-ACT: Imitation Learning with Adaptive Cartesian Tracking Control for a 30-ton Excavator
Mehdi Heydari Shahna, Seihun Kim, Soyi Jung +3
Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty. We propose imitation learning and adaptive Cartesian tracking (IL-ACT), a novel mo…
hoBIT: A Profile-Aware Retrieval-Augmented Chatbot for University Academic Advising
Yoonseo Kim, Seongmin Lee, Joongheon Kim +1
In university academic advising, identical questions can require different answers depending on a student's department, admission cohort, and degree program, causing profile-blind…
Hierarchical Multi-Agent Reinforcement Learning for Carbon-Aware AI Data Centers in Power Distribution Systems
Hyunsoo Lee, Panggah Prabawa, Dae-Hyun Choi +1
Eco-friendly energy management for artificial intelligence data centers (AIDCs) is crucial because of the significant increase in energy consumption-induced carbon emissions from A…
How Can Quantum Deep Learning Improve Large Language Models?
Emily Jimin Roh, Hyojun Ahn, Samuel Yen-Chi Chen +2
The rapid progress of large language models (LLMs) has transformed natural language processing, yet the challenge of efficient adaptation remains unresolved. Full fine-tuning achie…
Quantum Circuit Structure Optimization for Quantum Reinforcement Learning
Seok Bin Son, Joongheon Kim
Reinforcement learning (RL) enables agents to learn optimal policies through environmental interaction. However, RL suffers from reduced learning efficiency due to the curse of dim…
Hallucination-Aware Generative Pretrained Transformer for Cooperative Aerial Mobility Control
Hyojun Ahn, Seungcheol Oh, Gyu Seon Kim +3
This paper proposes SafeGPT, a two-tiered framework that integrates generative pretrained transformers (GPTs) with reinforcement learning (RL) for efficient and reliable unmanned a…
Double-Side Polarization and Beamforming Alignment in Polarization Reconfigurable MISO System with Deep Neural Networks
Seungcheol Oh, Han Han, Joongheon Kim +1
Polarization reconfigurable (PR) antennas enhance spectrum and energy efficiency between next-generation node B(gNB) and user equipment (UE). This is achieved by tuning the polariz…
Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks
Gyu Seon Kim, Yeryeong Cho, Jaehyun Chung +4
Achieving global space-air-ground integrated network (SAGIN) access only with CubeSats presents significant challenges such as the access sustainability limitations in specific reg…
Diffusion-based Quantum Error Mitigation using Stochastic Differential Equation
Joo Yong Shim, Joongheon Kim
Unlike closed systems, where the total energy and information are conserved within the system, open systems interact with the external environment which often leads to complex beha…
Quantum Neural Network Software Testing, Analysis, and Code Optimization for Advanced IoT Systems: Design, Implementation, and Visualization
Soohyun Park, Joongheon Kim
This paper introduces a novel run-time testing, analysis, and code optimization (TACO) method for quantum neural network (QNN) software in advanced Internet-of-Things (IoT) systems…
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications
Hankyul Baek, Donghyeon Kim, Joongheon Kim
Spurred by consistent advances and innovation in deep learning, object detection applications have become prevalent, particularly in autonomous driving that leverages various visua…
Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperation
Soohyun Park, Jae Pyoung Kim, Chanyoung Park +2
For Industry 4.0 Revolution, cooperative autonomous mobility systems are widely used based on multi-agent reinforcement learning (MARL). However, the MARL-based algorithms suffer f…
Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems
Chanyoung Park, Won Joon Yun, Jae Pyoung Kim +4
This paper proposes a novel algorithm, named quantum multi-agent actor-critic networks (QMACN) for autonomously constructing a robust mobile access system employing multiple unmann…
Software Simulation and Visualization of Quantum Multi-Drone Reinforcement Learning
Chanyoung Park, Jae Pyoung Kim, Won Joon Yun +3
Quantum machine learning (QML) has received a lot of attention according to its light training parameter numbers and speeds; and the advances of QML lead to active research on quan…
Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility
Chanyoung Park, Soohyun Park, Gyu Seon Kim +3
It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation. By…
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control
Won Joon Yun, Soohyun Park, Joongheon Kim +4
CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments. This paper creates a case where the UAVs with…
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation
Yunseok Kwak, Won Joon Yun, Soyi Jung +2
The emergence of quantum computing enables for researchers to apply quantum circuit on many existing studies. Utilizing quantum circuit and quantum differential programming, many r…
Quantum Scheduling for Millimeter-Wave Observation Satellite Constellation
Joongheon Kim, Yunseok Kwak, Soyi Jung +1
In beyond 5G and 6G network scenarios, the use of satellites has been actively discussed for extending target monitoring areas, even for extreme circumstances, where the monitoring…
Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations
Gusang Lee, Won Joon Yun, Soyi Jung +2
This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is use…