Výsledky vyhledávání - "training methodology"

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Exploring Large Language Models on Cross-Cultural Values in Connection with Training Methodology

Large language models (LLMs) closely interact with humans, and thus need an intimate understanding of the cultural values of human society. In this paper, we explore how open-source LLMs make judgments on diverse categories of cultural values across

Externí odkaz: http://arxiv.org/abs/2412.08846

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Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology

Autor: Tran, Son Quoc, Kretchmar, Matt

This paper proposes a novel training method to improve the robustness of Extractive Question Answering (EQA) models. Previous research has shown that existing models, when trained on EQA datasets that include unanswerable questions, demonstrate a sig

Externí odkaz: http://arxiv.org/abs/2409.19766

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Progressive DeepSSM: Training Methodology for Image-To-Shape Deep Models

Autor: Aziz, Abu Zahid Bin, Adams, Jadie, Elhabian, Shireen

Statistical shape modeling (SSM) is an enabling quantitative tool to study anatomical shapes in various medical applications. However, directly using 3D images in these applications still has a long way to go. Recent deep learning methods have paved

Externí odkaz: http://arxiv.org/abs/2310.01529

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Akademický článek

Architectural insights into and training methodology optimization of Pangu-Weather

Autor: D. To, J. Quinting, G. A. Hoshyaripour, M. Götz, A. Streit, C. Debus

Publikováno v: Geoscientific Model Development, Vol 17, Pp 8873-8884 (2024)

Data-driven medium-range weather forecasts have recently outperformed classical numerical weather prediction models, with Pangu-Weather (PGW) being the first breakthrough model to achieve this. The Transformer-based PGW introduced novel architectural

Externí odkaz: https://doaj.org/article/f99173ad8cfe45169c71bce43b7a1aac