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Emily Jimin Roh

2 accepted papers

2026

HOW CAN QUANTUM DEEP LEARNING IMPROVE LARGE LANGUAGE MODELS?

ICASSP 2026oral

The rapid progress of large language models (LLMs) has transformed natural language processing, yet the challenge of efficient adaptation remains unresolved. Full fine-tuning achieves strong performance but imposes prohibitive computational and memory costs. Parameter-efficient fine-tuning (PEFT) st…

Cited by 0SourcePDFScholar
2025

Hybrid Quantum-Classical Style Transfer (Student Abstract)

AAAI 2025technical

This paper proposes a novel quantum style transfer (QST) in hybrid quantum-classical computing. QST leverages quantum computing's ability to process high-dimensional data efficiently. Our approach aims to decrease both inference time and complexity while maintaining performance, presenting a viable…