5 papers
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…