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pro vyhledávání: '"KIM, JUNE"'
Autor:
Kim, June-Young, Weiss, Christian
We study the nonperturbative properties of the nucleon's chiral-odd generalized parton distributions (transversity GPDs) in the large-$N_c$ limit of QCD. This includes the parametric ordering of the spin-flavor components, the polynomiality property
Externí odkaz:
http://arxiv.org/abs/2411.17634
Publikováno v:
Proceedings of the ACM on Programming Languages, Volume 8, 2024; Issue OOPSLA2 Article No.: 288, Pages 468 - 498
Large language models (LLMs) have reshaped the landscape of program synthesis. However, contemporary LLM-based code completion systems often hallucinate broken code because they lack appropriate context, particularly when working with definitions not
Externí odkaz:
http://arxiv.org/abs/2409.00921
Autor:
Park, Jong Yoon, Kim, June Young
We report on investigations of mode coupling between rotating spokes during the onset of the breathing oscillation. Demonstrating the existence of nonlinear coupling between the sporadic spokes and the breathing oscillation, we suggest the oscillatin
Externí odkaz:
http://arxiv.org/abs/2406.13134
Respiratory sound classification (RSC) is challenging due to varied acoustic signatures, primarily influenced by patient demographics and recording environments. To address this issue, we introduce a text-audio multimodal model that utilizes metadata
Externí odkaz:
http://arxiv.org/abs/2406.06786
Recent advancements in AI have democratized its deployment as a healthcare assistant. While pretrained models from large-scale visual and audio datasets have demonstrably generalized to this task, surprisingly, no studies have explored pretrained spe
Externí odkaz:
http://arxiv.org/abs/2405.02996
We study the twist-3 spin-orbit correlations of quarks described by the nucleon matrix elements of the parity-odd rank-2 tensor QCD operator (the parity-odd partner of the QCD energy-momentum tensor). Our treatment is based on the effective dynamics
Externí odkaz:
http://arxiv.org/abs/2403.07186
Despite the remarkable advances in deep learning technology, achieving satisfactory performance in lung sound classification remains a challenge due to the scarcity of available data. Moreover, the respiratory sound samples are collected from a varie
Externí odkaz:
http://arxiv.org/abs/2312.09603
Deep generative models have emerged as a promising approach in the medical image domain to address data scarcity. However, their use for sequential data like respiratory sounds is less explored. In this work, we propose a straightforward approach to
Externí odkaz:
http://arxiv.org/abs/2311.06480
Autor:
Kim, June-Young, Weiss, Christian
The instanton vacuum picture is used to study hadronic matrix elements of the twist-3 (dimension-4, spin-1) QCD operators measuring the quark spin density and spin-orbit correlations. The QCD operators are converted to effective operators in the low-
Externí odkaz:
http://arxiv.org/abs/2310.16890
We investigate the gravitational form factors (GFFs) of the nucleon and the baryon octet, decomposed into their flavor components, utilizing a pion mean-field approach grounded in the large $N_c$ limit of Quantum Chromodynamics (QCD). Our focus is on
Externí odkaz:
http://arxiv.org/abs/2310.04670