Search Results for author: Hyelin Nam

Found 5 papers, 0 papers with code

Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing

no code implementations30 Nov 2023 Hyelin Nam, Gihyun Kwon, Geon Yeong Park, Jong Chul Ye

A promising recent approach in this realm is Delta Denoising Score (DDS) - an image editing technique based on Score Distillation Sampling (SDS) framework that leverages the rich generative prior of text-to-image diffusion models.

Contrastive Learning Denoising +2

Language-Oriented Communication with Semantic Coding and Knowledge Distillation for Text-to-Image Generation

no code implementations20 Sep 2023 Hyelin Nam, Jihong Park, Jinho Choi, Mehdi Bennis, Seong-Lyun Kim

By integrating recent advances in large language models (LLMs) and generative models into the emerging semantic communication (SC) paradigm, in this article we put forward to a novel framework of language-oriented semantic communication (LSC).

In-Context Learning Knowledge Distillation +1

Sequential Semantic Generative Communication for Progressive Text-to-Image Generation

no code implementations8 Sep 2023 Hyelin Nam, Jihong Park, Jinho Choi, Seong-Lyun Kim

Our work is expected to pave a new road of utilizing state-of-the-art generative models to real communication systems

Sentence Text-to-Image Generation

Differentially Private CutMix for Split Learning with Vision Transformer

no code implementations28 Oct 2022 Seungeun Oh, Jihong Park, Sihun Baek, Hyelin Nam, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim

Split learning (SL) detours this by communicating smashed data at a cut-layer, yet suffers from data privacy leakage and large communication costs caused by high similarity between ViT' s smashed data and input data.

Federated Learning Privacy Preserving

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