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pro vyhledávání: '"Schulz, Alexander"'
Pretraining language models on large text corpora is a common practice in natural language processing. Fine-tuning of these models is then performed to achieve the best results on a variety of tasks. In this paper, we investigate the problem of catas
Externí odkaz:
http://arxiv.org/abs/2404.01317
Over the last years, various sentence embedders have been an integral part in the success of current machine learning approaches to Natural Language Processing (NLP). Unfortunately, multiple sources have shown that the bias, inherent in the datasets
Externí odkaz:
http://arxiv.org/abs/2403.18555
Attention based Large Language Models (LLMs) are the state-of-the-art in natural language processing (NLP). The two most common architectures are encoders such as BERT, and decoders like the GPT models. Despite the success of encoder models, on which
Externí odkaz:
http://arxiv.org/abs/2403.18872
Plenty of works have brought social biases in language models to attention and proposed methods to detect such biases. As a result, the literature contains a great deal of different bias tests and scores, each introduced with the premise to uncover y
Externí odkaz:
http://arxiv.org/abs/2401.15499
Autor:
Schulz, Alexander
Der vorliegende Artikel nähert sich der Frage, welche Bedingungen Hochschulen erfüllen müssen, um E-Assessments anbieten zu können. Er bietet Hinweise darauf, welche technischen und bauplanerischen Bedingungen erfüllt sein sollten, um diese nach
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A30319
https://tud.qucosa.de/api/qucosa%3A30319/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A30319/attachment/ATT-0/
Autor:
Schulz, Alexander
Der vorliegende Artikel nähert sich der Frage, welche Bedingungen Hochschulen erfüllen müssen, um E-Assessments anbieten zu können. Er bietet Hinweise darauf, welche technischen und bauplanerischen Bedingungen erfüllt sein sollten, um diese nach
Autor:
Padash, Amin, Aghion, Erez, Schulz, Alexander, Barkai, Eli, Chechkin, Aleksei V, Metzler, Ralf, Kantz, Holger
Publikováno v:
New J. Phys. 24 (2022) 073026
We perform numerical studies of a thermally driven, overdamped particle in a random quenched force field, known as the Sinai model. We compare the unbounded motion on an infinite 1-dimensional domain to the motion in bounded domains with reflecting b
Externí odkaz:
http://arxiv.org/abs/2207.02936
Dimensionality reduction is a popular preprocessing and a widely used tool in data mining. Transparency, which is usually achieved by means of explanations, is nowadays a widely accepted and crucial requirement of machine learning based systems like
Externí odkaz:
http://arxiv.org/abs/2206.07391
Autor:
Rüscher, Claus Henning, Kiesel, Florian, Schulz, Alexander, Schomborg, Lars, Buhl, Josef-Christian
Publikováno v:
Diffusion fundamentals. 24(43):1-2