Zobrazeno 1 - 10
of 688
pro vyhledávání: '"Kim, Tae‐Soo"'
When developing Computer Aided Detection (CAD) systems for Digital Breast Tomosynthesis (DBT), the complexity arising from the volumetric nature of the modality poses significant technical challenges for obtaining large-scale accurate annotations. Wi
Externí odkaz:
http://arxiv.org/abs/2409.16581
This paper aims to adapt the source model to the target environment, leveraging small user feedback (i.e., labeled target data) readily available in real-world applications. We find that existing semi-supervised domain adaptation (SemiSDA) methods of
Externí odkaz:
http://arxiv.org/abs/2407.15383
Autor:
Lee, Yoonjoo, Son, Kihoon, Kim, Tae Soo, Kim, Jisu, Chung, John Joon Young, Adar, Eytan, Kim, Juho
As Large Language Models (LLMs) are nondeterministic, the same input can generate different outputs, some of which may be incorrect or hallucinated. If run again, the LLM may correct itself and produce the correct answer. Unfortunately, most LLM-powe
Externí odkaz:
http://arxiv.org/abs/2405.05581
Autor:
Son, Kihoon, Kwon, Jinhyeon, Choi, DaEun, Kim, Tae Soo, Kim, Young-Ho, Yun, Sangdoo, Kim, Juho
With the advancement of Large-Language Models (LLMs) and Large Vision-Language Models (LVMs), agents have shown significant capabilities in various tasks, such as data analysis, gaming, or code generation. Recently, there has been a surge in research
Externí odkaz:
http://arxiv.org/abs/2405.04497
Despite the growing demand for professional graphic design knowledge, the tacit nature of design inhibits knowledge sharing. However, there is a limited understanding on the characteristics and instances of tacit knowledge in graphic design. In this
Externí odkaz:
http://arxiv.org/abs/2403.06252
Designers rely on visual search to explore and develop ideas in early design stages. However, designers can struggle to identify suitable text queries to initiate a search or to discover images for similarity-based search that can adequately express
Externí odkaz:
http://arxiv.org/abs/2310.01287
By simply composing prompts, developers can prototype novel generative applications with Large Language Models (LLMs). To refine prototypes into products, however, developers must iteratively revise prompts by evaluating outputs to diagnose weaknesse
Externí odkaz:
http://arxiv.org/abs/2309.13633
Research consumption has been traditionally limited to the reading of academic papers-a static, dense, and formally written format. Alternatively, pre-recorded conference presentation videos, which are more dynamic, concise, and colloquial, have rece
Externí odkaz:
http://arxiv.org/abs/2308.15224
Publikováno v:
Appl. Phys. Lett. 123, 023502 (2023)
Graphene, with its unique band structure, mechanical stability, and high charge mobility, holds great promise for next-generation electronics. Nevertheless, its zero band gap challenges the control of current flow through electrical gating, consequen
Externí odkaz:
http://arxiv.org/abs/2306.14501
Deep learning has shown great potential in assisting radiologists in reading chest X-ray (CXR) images, but its need for expensive annotations for improving performance prevents widespread clinical application. Visual language pre-training (VLP) can a
Externí odkaz:
http://arxiv.org/abs/2304.05303