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pro vyhledávání: '"contextual word embeddings"'
Pretrained language model (PLM) hidden states are frequently employed as contextual word embeddings (CWE): high-dimensional representations that encode semantic information given linguistic context. Across many areas of computational linguistics rese
Externí odkaz:
http://arxiv.org/abs/2408.04162
Akademický článek
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Adding interpretability to word embeddings represents an area of active research in text representation. Recent work has explored thepotential of embedding words via so-called polar dimensions (e.g. good vs. bad, correct vs. wrong). Examples of such
Externí odkaz:
http://arxiv.org/abs/2301.04704
Akademický článek
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Autor:
Agmon S; Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel., Singer U; Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel., Radinsky K; Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.
Publikováno v:
JMIR AI [JMIR AI] 2024 Oct 02; Vol. 3, pp. e49546. Date of Electronic Publication: 2024 Oct 02.
Autor:
Pilaluisa, José1 (AUTHOR), Tomás, David2 (AUTHOR) dtomas@dlsi.ua.es, Navarro-Colorado, Borja2 (AUTHOR), Mazón, Jose-Norberto2 (AUTHOR)
Publikováno v:
Neural Computing & Applications. May2023, Vol. 35 Issue 13, p9319-9333. 15p.
Detecting lexical semantic change in smaller data sets, e.g. in historical linguistics and digital humanities, is challenging due to a lack of statistical power. This issue is exacerbated by non-contextual embedding models that produce one embedding
Externí odkaz:
http://arxiv.org/abs/2104.03776
The Web has become the main platform where people express their opinions about entities of interest and their associated aspects. Aspect-Based Sentiment Analysis (ABSA) aims to automatically compute the sentiment towards these aspects from opinionate
Externí odkaz:
http://arxiv.org/abs/2004.08673
In this work, we examine the extent to which embeddings may encode marginalized populations differently, and how this may lead to a perpetuation of biases and worsened performance on clinical tasks. We pretrain deep embedding models (BERT) on medical
Externí odkaz:
http://arxiv.org/abs/2003.11515
Image Captioning, or the automatic generation of descriptions for images, is one of the core problems in Computer Vision and has seen considerable progress using Deep Learning Techniques. We propose to use Inception-ResNet Convolutional Neural Networ
Externí odkaz:
http://arxiv.org/abs/2102.11237