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pro vyhledávání: '"Koo, A"'
Text-based diffusion video editing systems have been successful in performing edits with high fidelity and textual alignment. However, this success is limited to rigid-type editing such as style transfer and object overlay, while preserving the origi
Externí odkaz:
http://arxiv.org/abs/2409.13037
Autor:
Koo, Junghyun, Kim, Chinkyo
SiC structures, including nanowires and films, can be effectively grown on Si substrates through carbonization. However, growth parameters other than temperature, which influence the preferential formation of SiC nanowires or films, have not yet been
Externí odkaz:
http://arxiv.org/abs/2409.09233
Autor:
Mancusi, Michele, Halychanskyi, Yurii, Cheuk, Kin Wai, Lai, Chieh-Hsin, Uhlich, Stefan, Koo, Junghyun, Martínez-Ramírez, Marco A., Liao, Wei-Hsiang, Fabbro, Giorgio, Mitsufuji, Yuhki
Music timbre transfer is a challenging task that involves modifying the timbral characteristics of an audio signal while preserving its melodic structure. In this paper, we propose a novel method based on dual diffusion bridges, trained using the Coc
Externí odkaz:
http://arxiv.org/abs/2409.06096
Autor:
Koo, Dowan, Song, Sihyun
We establish global existence of mild solutions to the BGK model proposed by Bouchut [J. Stat. Phys., 95, (1999), 113--170] under the minimal assumption of finite kinetic entropy initial data. Moreover we rigorously derive a kinetic entropy inequalit
Externí odkaz:
http://arxiv.org/abs/2409.04129
To overcome the burden on the memory size and bandwidth due to ever-increasing size of large language models (LLMs), aggressive weight quantization has been recently studied, while lacking research on quantizing activations. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2409.05902
When discussing difficult topics online, is it common to meaningfully engage with people from diverse perspectives? Why or why not? Could features of the online environment be redesigned to encourage civil conversation across difference? In this pape
Externí odkaz:
http://arxiv.org/abs/2409.03989
Deep learning models have shown promise in histopathology image analysis, but their opaque decision-making process poses challenges in high-risk medical scenarios. Here we introduce HIPPO, an explainable AI method that interrogates attention-based mu
Externí odkaz:
http://arxiv.org/abs/2409.03080
Keyphrase Prediction (KP) is essential for identifying keyphrases in a document that can summarize its content. However, recent Natural Language Processing (NLP) advances have developed more efficient KP models using deep learning techniques. The lim
Externí odkaz:
http://arxiv.org/abs/2409.01087
A high-brightness entangled photon pair (HBEPP) source is essential for conducting entanglement-based quantum key distribution (QKD) between a satellite and a ground station. While an ultrabright source can overcome significant losses in satellite-ba
Externí odkaz:
http://arxiv.org/abs/2408.14768
Autor:
Cao, Zi-Yu, Wang, Honghong, Park, Chan-Koo, Park, Tae Beom, Jang, Harim, Seo, Soonbeom, Kim, Sung-Il, Park, Tuson
The evolution of the Fermi surface across the quantum critical point (QCP), which is relevant for characterizing the quantum criticality and understanding its relation with unconventional superconductivity, is an intriguing subject in the study of st
Externí odkaz:
http://arxiv.org/abs/2408.13604