Zobrazeno 1 - 10
of 820
pro vyhledávání: '"Pokropek At"'
This paper investigates the presence of political bias in emotion inference models used for sentiment analysis (SA) in social science research. Machine learning models often reflect biases in their training data, impacting the validity of their outco
Externí odkaz:
http://arxiv.org/abs/2407.13891
This study explores the use of large language models (LLMs) to predict emotion intensity in Polish political texts, a resource-poor language context. The research compares the performance of several LLMs against a supervised model trained on an annot
Externí odkaz:
http://arxiv.org/abs/2407.12141
In this work, we present a pipeline to reconstruct the 3D pose of a horse from 4 simultaneous surveillance camera recordings. Our environment poses interesting challenges to tackle, such as limited field view of the cameras and a relatively closed an
Externí odkaz:
http://arxiv.org/abs/2306.05311
Autor:
Pokropek, Artur, Pokropek, Ernest
Publikováno v:
Structural Equation Modeling: A Multidisciplinary Journal 2022
While in recent years a number of new statistical approaches have been proposed to model group differences with a different assumption on the nature of the measurement invariance of the instruments, the tools for detecting local misspecifications of
Externí odkaz:
http://arxiv.org/abs/2107.12757
Autor:
Jorge Pokropek
Publikováno v:
Area, Vol 30, Iss 1 (2024)
Externí odkaz:
https://doaj.org/article/7469910c696c4136a680f260b977f3ff
Autor:
Katarzyna Chyl, Agnieszka Dębska, Artur Pokropek, Marcin Szczerbiński, Łukasz Lech Tanaś, Michał Sitek
Publikováno v:
Frontiers in Education, Vol 9 (2024)
The paper reviews the methods for assessing different components of reading skills in adults with reading difficulties, along with functional reading skills. We are particularly interested in the assessment methods available to researchers and practi
Externí odkaz:
https://doaj.org/article/a3307922601146d59756c14e9e042314
Most action recognition models today are highly parameterized, and evaluated on datasets with appearance-wise distinct classes. It has also been shown that 2D Convolutional Neural Networks (CNNs) tend to be biased toward texture rather than shape in
Externí odkaz:
http://arxiv.org/abs/2112.12175
Publikováno v:
In Computers & Education July 2023 200
Autor:
Cachay, Salva Rühling, Erickson, Emma, Bucker, Arthur Fender C., Pokropek, Ernest, Potosnak, Willa, Bire, Suyash, Osei, Salomey, Lütjens, Björn
Deep learning-based models have recently outperformed state-of-the-art seasonal forecasting models, such as for predicting El Ni\~no-Southern Oscillation (ENSO). However, current deep learning models are based on convolutional neural networks which a
Externí odkaz:
http://arxiv.org/abs/2104.05089
Publikováno v:
In Computers & Education January 2024 208