Zobrazeno 1 - 10
of 5 256
pro vyhledávání: '"Sungchul On"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Accurate measurement of abdominal aortic aneurysm is essential for selecting suitable stent-grafts to avoid complications of endovascular aneurysm repair. However, the conventional image-based measurements are inaccurate and time-consuming.
Externí odkaz:
https://doaj.org/article/4e31d6dde9224ff78b7bb5916914ed7b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Accurate lesion diagnosis through computed tomography (CT) and advances in laparoscopic or robotic surgeries have increased partial nephrectomy survival rates. However, accurately marking the kidney resection area through the laparoscope is
Externí odkaz:
https://doaj.org/article/ae75ae07273b4c618cc7640a08f62f4f
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract Partial nephrectomy has been demonstrated to preserve renal function compared with radical nephrectomy. Computed tomography (CT) is used to reveal localized renal cell carcinoma (RCC). However, marking RCC directly and quantitatively on a pa
Externí odkaz:
https://doaj.org/article/fadd704cf3494762a2dcc79e10ffd2dd
Autor:
Luera, Reuben, Rossi, Ryan, Dernoncourt, Franck, Siu, Alexa, Kim, Sungchul, Yu, Tong, Zhang, Ruiyi, Chen, Xiang, Lipka, Nedim, Zhang, Zhehao, Kim, Seon Gyeom, Lee, Tak Yeon
In this work, we research user preferences to see a chart, table, or text given a question asked by the user. This enables us to understand when it is best to show a chart, table, or text to the user for the specific question. For this, we conduct a
Externí odkaz:
http://arxiv.org/abs/2411.07451
Autor:
Zhang, Zhehao, Rossi, Ryan A., Kveton, Branislav, Shao, Yijia, Yang, Diyi, Zamani, Hamed, Dernoncourt, Franck, Barrow, Joe, Yu, Tong, Kim, Sungchul, Zhang, Ruiyi, Gu, Jiuxiang, Derr, Tyler, Chen, Hongjie, Wu, Junda, Chen, Xiang, Wang, Zichao, Mitra, Subrata, Lipka, Nedim, Ahmed, Nesreen, Wang, Yu
Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on personalized LLMs have focused either entirely on (a) per
Externí odkaz:
http://arxiv.org/abs/2411.00027
Autor:
Luera, Reuben, Rossi, Ryan A., Siu, Alexa, Dernoncourt, Franck, Yu, Tong, Kim, Sungchul, Zhang, Ruiyi, Chen, Xiang, Salehy, Hanieh, Zhao, Jian, Basu, Samyadeep, Mathur, Puneet, Lipka, Nedim
The applications of generative AI have become extremely impressive, and the interplay between users and AI is even more so. Current human-AI interaction literature has taken a broad look at how humans interact with generative AI, but it lacks specifi
Externí odkaz:
http://arxiv.org/abs/2410.22370
Autor:
Van Nguyen, Chien, Shen, Xuan, Aponte, Ryan, Xia, Yu, Basu, Samyadeep, Hu, Zhengmian, Chen, Jian, Parmar, Mihir, Kunapuli, Sasidhar, Barrow, Joe, Wu, Junda, Singh, Ashish, Wang, Yu, Gu, Jiuxiang, Dernoncourt, Franck, Ahmed, Nesreen K., Lipka, Nedim, Zhang, Ruiyi, Chen, Xiang, Yu, Tong, Kim, Sungchul, Deilamsalehy, Hanieh, Park, Namyong, Rimer, Mike, Zhang, Zhehao, Yang, Huanrui, Rossi, Ryan A., Nguyen, Thien Huu
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, making them ideal for various settings including on-device, mobile, edge d
Externí odkaz:
http://arxiv.org/abs/2410.20011
Autor:
Zhang, Zhehao, Rossi, Ryan, Yu, Tong, Dernoncourt, Franck, Zhang, Ruiyi, Gu, Jiuxiang, Kim, Sungchul, Chen, Xiang, Wang, Zichao, Lipka, Nedim
While vision-language models (VLMs) have demonstrated remarkable performance across various tasks combining textual and visual information, they continue to struggle with fine-grained visual perception tasks that require detailed pixel-level analysis
Externí odkaz:
http://arxiv.org/abs/2410.16400
Large language models (LLMs) have been used to generate query expansions augmenting original queries for improving information search. Recent studies also explore providing LLMs with initial retrieval results to generate query expansions more grounde
Externí odkaz:
http://arxiv.org/abs/2410.13765
In this paper, we present an effective data augmentation framework leveraging the Large Language Model (LLM) and Diffusion Model (DM) to tackle the challenges inherent in data-scarce scenarios. Recently, DMs have opened up the possibility of generati
Externí odkaz:
http://arxiv.org/abs/2409.16949