Sökning: "token embedding"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden token embedding.

1. 1. Data Collection and Layout Analysis on Visually Rich Documents using Multi-Modular Deep Learning.

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mattias Stahre; [2022]
   Nyckelord :DeepLearning; Machine Learning; Dataset Collection; Annotation; Labeling; Transformer Network; Multi-Modal; Computer Vision; Natural Language Processing; Embedding; LayoutLMv2; DocBank; Djupinlärning; Maskininlärning; Datasamling; Annotering; Märkning; Transformernätverk; Multi-modulär; Datorsyn; Naturlig Språkbehandling; Inbäddning; LayoutLMv2; DocBank;

   Sammanfattning : The use of Deep Learning methods for Document Understanding has been embraced by the research community in recent years. A requirement for Deep Learning methods and especially Transformer Networks, is access to large datasets. LÄS MER

3. 2. Optimizing the Performance of Text Classification Models by Improving the Isotropy of the Embeddings using a Joint Loss Function

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Joseph Attieh; [2022]
   Nyckelord :Text Classification; Isotropy; Embeddings; BERT; IsoScore; Klassificering av Text; Isotropi; Inbäddningar; BERT; IsoScore;

   Sammanfattning : Recent studies show that the spatial distribution of the sentence representations generated from pre-trained language models is highly anisotropic, meaning that the representations are not uniformly distributed among the directions of the embedding space. Thus, the expressiveness of the embedding space is limited, as the embeddings are less distinguishable and less diverse. LÄS MER

4. 3. Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Spyridon Dimitriadis; [2021]
   Nyckelord :multi-task regression; QSAR; QSPR; deep learning; attention based models; transfer learning;

   Sammanfattning : With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. LÄS MER

5. 4. Unsupervised Lexical Semantic Change Detection with Context-Dependent Word Representations

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Huiling You; [2021]
   Nyckelord :;

   Sammanfattning : In this work, we explore the usefulness of contextualized embeddings from language models on lexical semantic change (LSC) detection. With diachronic corpora spanning two time periods, we construct word embeddings for a selected set of target words, aiming at detecting potential LSC of each target word across time. LÄS MER

7. 5. French AXA Insurance Word Embeddings : Effects of Fine-tuning BERT and Camembert on AXA France’s data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Hend Zouari; [2020]
   Nyckelord :NLP; Language model; Word embedding; BERT; camemBERT; NLP; Language model; Word embedding; BERT; camemBERT;

   Sammanfattning : We explore in this study the different Natural Language Processing state-of-the art technologies that allow transforming textual data into numerical representation. We go through the theory of the existing traditional methods as well as the most recent ones. LÄS MER