Zobrazeno 1 - 10
of 2 392
pro vyhledávání: '"Kang, Bo"'
Estimation of distribution algorithms (EDAs) constitute a new branch of evolutionary optimization algorithms, providing effective and efficient optimization performance in a variety of research areas. Recent studies have proposed new EDAs that employ
Externí odkaz:
http://arxiv.org/abs/2407.18257
Personalized recommendation systems often drive users towards more extreme content, exacerbating opinion polarization. While (content-aware) moderation has been proposed to mitigate these effects, such approaches risk curtailing the freedom of speech
Externí odkaz:
http://arxiv.org/abs/2405.18941
KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes key excerpts from parliamentary proceedings, followed by the potential f
Externí odkaz:
http://arxiv.org/abs/2404.17597
Autor:
Jeon, Sanghoon, Lee, Hyo-Geon, Lee, Jae-Sung, Kang, Bo-Min, Jeon, Byung-Wook, Yoon, Jun Young, Hyun, Jae-Sang
In phase-shifting profilometry (PSP), any motion during the acquisition of fringe patterns can introduce errors because it assumes both the object and measurement system are stationary. Therefore, we propose a method to pixel-wise reduce the errors w
Externí odkaz:
http://arxiv.org/abs/2401.15938
Autor:
Park, Jong-Yeon, Ju, Jang-Won, Lee, Wonil, Kang, Bo-Gyeong, Kachi, Yasuyuki, Sakurai, Kouichi
As NIST is putting the final touches on the standardization of PQC (Post Quantum Cryptography) public key algorithms, it is a racing certainty that peskier cryptographic attacks undeterred by those new PQC algorithms will surface. Such a trend in tur
Externí odkaz:
http://arxiv.org/abs/2311.08625
In settings such as e-recruitment and online dating, recommendation involves distributing limited opportunities, calling for novel approaches to quantify and enforce fairness. We introduce \emph{inferiority}, a novel (un)fairness measure quantifying
Externí odkaz:
http://arxiv.org/abs/2311.04542
Automated occupation extraction and standardization from free-text job postings and resumes are crucial for applications like job recommendation and labor market policy formation. This paper introduces LLM4Jobs, a novel unsupervised methodology that
Externí odkaz:
http://arxiv.org/abs/2309.09708
Recommender systems may suffer from congestion, meaning that there is an unequal distribution of the items in how often they are recommended. Some items may be recommended much more than others. Recommenders are increasingly used in domains where ite
Externí odkaz:
http://arxiv.org/abs/2308.09516
We present SkillGPT, a tool for skill extraction and standardization (SES) from free-style job descriptions and user profiles with an open-source Large Language Model (LLM) as backbone. Most previous methods for similar tasks either need supervision
Externí odkaz:
http://arxiv.org/abs/2304.11060