Zobrazeno 1 - 10
of 9 023
pro vyhledávání: '"An, SangWoo"'
As the use of machine learning models has increased, numerous studies have aimed to enhance fairness. However, research on the intersection of fairness and explainability remains insufficient, leading to potential issues in gaining the trust of actua
Externí odkaz:
http://arxiv.org/abs/2412.17523
Autor:
Jang, Hyesu, Yang, Wooseong, Kim, Hanguen, Lee, Dongje, Kim, Yongjin, Park, Jinbum, Jeon, Minsoo, Koh, Jaeseong, Kang, Yejin, Jung, Minwoo, Jung, Sangwoo, Hao, Chng Zhen, Hin, Wong Yu, Yihang, Chew, Kim, Ayoung
Maritime environmental sensing requires overcoming challenges from complex conditions such as harsh weather, platform perturbations, large dynamic objects, and the requirement for long detection ranges. While cameras and LiDAR are commonly used in gr
Externí odkaz:
http://arxiv.org/abs/2412.03887
Employing large language models (LLMs) to enable embodied agents has become popular, yet it presents several limitations in practice. In this work, rather than using LLMs directly as agents, we explore their use as tools for embodied agent learning.
Externí odkaz:
http://arxiv.org/abs/2411.17135
Autor:
Kang, Donggoo, Jeong, Dasol, Lee, Hyunmin, Park, Sangwoo, Park, Hasil, Kwon, Sunkyu, Kim, Yeongjoon, Paik, Joonki
The Large Vision Language Model (VLM) has recently addressed remarkable progress in bridging two fundamental modalities. VLM, trained by a sufficiently large dataset, exhibits a comprehensive understanding of both visual and linguistic to perform div
Externí odkaz:
http://arxiv.org/abs/2411.18038
Bayesian optimization (BO) is a sequential approach for optimizing black-box objective functions using zeroth-order noisy observations. In BO, Gaussian processes (GPs) are employed as probabilistic surrogate models to estimate the objective function
Externí odkaz:
http://arxiv.org/abs/2411.17387
We investigate the inverse scattering problem for tracking the location and orientation of a moving scatterer using a single incident field. We solve the problem by adopting the optimization approach with the objective function defined by the discrep
Externí odkaz:
http://arxiv.org/abs/2411.17233
Long-tailed image recognition is a computer vision problem considering a real-world class distribution rather than an artificial uniform. Existing methods typically detour the problem by i) adjusting a loss function, ii) decoupling classifier learnin
Externí odkaz:
http://arxiv.org/abs/2411.07621
Models trained with empirical risk minimization (ERM) are prone to be biased towards spurious correlations between target labels and bias attributes, which leads to poor performance on data groups lacking spurious correlations. It is particularly cha
Externí odkaz:
http://arxiv.org/abs/2411.01757
Radio resource allocation often calls for the optimization of black-box objective functions whose evaluation is expensive in real-world deployments. Conventional optimization methods apply separately to each new system configuration, causing the numb
Externí odkaz:
http://arxiv.org/abs/2410.19837
Autor:
Lee, Gisang, Park, Sangwoo, Park, Junyoung, Chung, Andrew, Park, Sieun, Park, Yoonah, Kim, Byungju, Cho, Min-gyu
Large Language Models (LLMs) have exhibited remarkable capabilities in many complex tasks including mathematical reasoning. However, traditional approaches heavily rely on ensuring self-consistency within single prompting method, which limits the exp
Externí odkaz:
http://arxiv.org/abs/2410.09780