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pro vyhledávání: '"Kim Dongyoung"'
An open challenge in recent machine learning is about how to improve the reasoning capability of large language models (LLMs) in a black-box setting, i.e., without access to detailed information such as output token probabilities. Existing approaches
Externí odkaz:
http://arxiv.org/abs/2406.18695
Self-supervised learning of image representations by predicting future frames is a promising direction but still remains a challenge. This is because of the under-determined nature of frame prediction; multiple potential futures can arise from a sing
Externí odkaz:
http://arxiv.org/abs/2406.07398
Aligning large language models (LLMs) with human preferences becomes a key component to obtaining state-of-the-art performance, but it yields a huge cost to construct a large human-annotated preference dataset. To tackle this problem, we propose a ne
Externí odkaz:
http://arxiv.org/abs/2406.04412
In no-reference image quality assessment (NR-IQA), the challenge of limited dataset sizes hampers the development of robust and generalizable models. Conventional methods address this issue by utilizing large datasets to extract rich representations
Externí odkaz:
http://arxiv.org/abs/2406.01020
White balance (WB) algorithms in many commercial cameras assume single and uniform illumination, leading to undesirable results when multiple lighting sources with different chromaticities exist in the scene. Prior research on multi-illuminant WB typ
Externí odkaz:
http://arxiv.org/abs/2402.18277
Publikováno v:
Volume: 21, Year: 2023, Page: 1-5
Recently, reference-based image super-resolution (RefSR) has shown excellent performance in image super-resolution (SR) tasks. The main idea of RefSR is to utilize additional information from the reference (Ref) image to recover the high-frequency co
Externí odkaz:
http://arxiv.org/abs/2401.15944
A promising technique for exploration is to maximize the entropy of visited state distribution, i.e., state entropy, by encouraging uniform coverage of visited state space. While it has been effective for an unsupervised setup, it tends to struggle i
Externí odkaz:
http://arxiv.org/abs/2305.19476
Autor:
Kim Dongyoung, Tang Mingchu, Wu Jiang, Hatch Sabina, Maidaniuk Yurii, Dorogan Vitaliy, Mazur Yuriy I., Salamo Gregory J., Liu Huiyun
Publikováno v:
E3S Web of Conferences, Vol 16, p 16001 (2017)
In this work, the effect of Si doping on InAs/GaAs quantum dot solar cells with AlAs cap layers is studied. The AlAs cap layers suppress the formation of the wetting layer during quantum dot growth. This helps achieve quantum dot state filling, which
Externí odkaz:
https://doaj.org/article/bd452a2eba0746d29adcf6f938ee0e45
Autor:
Duk Nam, Gyeong, Lim, Kisung, Lee, Heeji, Kim, Youchan, Kim, Dongyoung, Ju, Hyunchul, Hoon Joo, Jong
Publikováno v:
In Chemical Engineering Journal 1 November 2024 499
Autor:
Kim, Minkyoung, Hwang, Jeomshik, Montluçon, Daniel B., Haghipour, Negar, Kim, Dongyoung, Kim, Ho Jung, Choi, Ki Young, Kim, Chang Joon, Kang, Chang-Keun, Kim, Young-Il, Eglinton, Timothy I.
Publikováno v:
In Marine Pollution Bulletin August 2024 205