Zobrazeno 1 - 10
of 74 102
pro vyhledávání: '"KIM, JIN"'
Text-to-image (T2I) models can effectively capture the content or style of reference images to perform high-quality customization. A representative technique for this is fine-tuning using low-rank adaptations (LoRA), which enables efficient model cus
Externí odkaz:
http://arxiv.org/abs/2412.09169
Autor:
Bedalov, Matt. J., Blakely, Matt, Buttler, Peter. D., Carnahan, Caitlin, Chong, Frederic T., Chung, Woo Chang, Cole, Dan C., Goiporia, Palash, Gokhale, Pranav, Heim, Bettina, Hickman, Garrett T., Jones, Eric B., Jones, Ryan A., Khalate, Pradnya, Kim, Jin-Sung, Kuper, Kevin W., Lichtman, Martin T., Lee, Stephanie, Mason, David, Neff-Mallon, Nathan A., Noel, Thomas W., Omole, Victory, Radnaev, Alexander G., Rines, Rich, Saffman, Mark, Shabtai, Efrat, Teo, Mariesa H., Thotakura, Bharath, Tomesh, Teague, Tucker, Angela K.
We report on the fault-tolerant operation of logical qubits on a neutral atom quantum computer, with logical performance surpassing physical performance for multiple circuits including Bell states (12x error reduction), random circuits (15x), and a p
Externí odkaz:
http://arxiv.org/abs/2412.07670
Autor:
Jang, Sooyong, Jang, Kuk Jin, Choi, Hyonyoung, Han, Yong-Seop, Lee, Seongjin, Kim, Jin-hyun, Lee, Insup
Timely detection and treatment are essential for maintaining eye health. Visual acuity (VA), which measures the clarity of vision at a distance, is a crucial metric for managing eye health. Machine learning (ML) techniques have been introduced to ass
Externí odkaz:
http://arxiv.org/abs/2412.06624
Text-based generation and editing of 3D scenes hold significant potential for streamlining content creation through intuitive user interactions. While recent advances leverage 3D Gaussian Splatting (3DGS) for high-fidelity and real-time rendering, ex
Externí odkaz:
http://arxiv.org/abs/2411.16443
Autor:
Alexeev, Yuri, Farag, Marwa H., Patti, Taylor L., Wolf, Mark E., Ares, Natalia, Aspuru-Guzik, Alán, Benjamin, Simon C., Cai, Zhenyu, Chandani, Zohim, Fedele, Federico, Harrigan, Nicholas, Kim, Jin-Sung, Kyoseva, Elica, Lietz, Justin G., Lubowe, Tom, McCaskey, Alexander, Melko, Roger G., Nakaji, Kouhei, Peruzzo, Alberto, Stanwyck, Sam, Tubman, Norm M., Wang, Hanrui, Costa, Timothy
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including th
Externí odkaz:
http://arxiv.org/abs/2411.09131
Learning generalized models from biased data is an important undertaking toward fairness in deep learning. To address this issue, recent studies attempt to identify and leverage bias-conflicting samples free from spurious correlations without prior k
Externí odkaz:
http://arxiv.org/abs/2411.00360
Verifying the violation of Bell's inequality is one of the most representative methods to demonstrate that entangled photon pairs prepared in a quantum optics-based system exhibit quantum properties. While experiments on Bell inequality violations ha
Externí odkaz:
http://arxiv.org/abs/2410.23689
In this study, we introduces a parameter-efficient model that outperforms traditional models in time series forecasting, by integrating High-order Polynomial Projection (HiPPO) theory into the Kolmogorov-Arnold network (KAN) framework. This HiPPO-KAN
Externí odkaz:
http://arxiv.org/abs/2410.14939
Large language models (LLMs) have demonstrated strong capabilities across various language tasks, notably through instruction-tuning methods. However, LLMs face challenges in visualizing complex, real-world data through charts and plots. Firstly, exi
Externí odkaz:
http://arxiv.org/abs/2410.04064
Autor:
Oh, Yujin, Park, Sangjoon, Li, Xiang, Yi, Wang, Paly, Jonathan, Efstathiou, Jason, Chan, Annie, Kim, Jun Won, Byun, Hwa Kyung, Lee, Ik Jae, Cho, Jaeho, Wee, Chan Woo, Shu, Peng, Wang, Peilong, Yu, Nathan, Holmes, Jason, Ye, Jong Chul, Li, Quanzheng, Liu, Wei, Koom, Woong Sub, Kim, Jin Sung, Kim, Kyungsang
Clinical experts employ diverse philosophies and strategies in patient care, influenced by regional patient populations. However, existing medical artificial intelligence (AI) models are often trained on data distributions that disproportionately ref
Externí odkaz:
http://arxiv.org/abs/2410.00046