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cs.CV2024
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
Wonguk Cho, Seokeon Choi, Debasmit Das +4
Recent advancements in text-to-image diffusion models have enabled the personalization of these models to generate custom images from textual prompts. This paper presents an effici…
cs.LG2024
Overcoming Data Inequality across Domains with Semi-Supervised Domain Generalization
Jinha Park, Wonguk Cho, Taesup Kim
While there have been considerable advancements in machine learning driven by extensive datasets, a significant disparity still persists in the availability of data across various…
cs.LG2024
X-PEFT: eXtremely Parameter-Efficient Fine-Tuning for Extreme Multi-Profile Scenarios
Namju Kwak, Taesup Kim
Parameter-efficient fine-tuning (PEFT) techniques, such as adapter tuning, aim to fine-tune a pre-trained language model (PLM) using a minimal number of parameters for a specific t…