Bidirectional Encoder representation from Image Transformers for recognizing sunflower diseases from photographs by V.A. Baboshina, P.A. Lyakhov, U.A. Lyakhova, V.A. Pismennyy

“…This paper proposes a modern system for recognizing sunflower diseases based on Bidirectional Encoder representation from Image Transformers (BEIT). …”
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Assessing Scientific Text Similarity: A Novel Approach Utilizing Non-Negative Matrix Factorization and Bidirectional Encoder Representations from Transformer by Zhixuan Jia, Wenfang Tian, Wang Li, Kai Song, Fuxin Wang, Congjing Ran

“…This approach integrates a patent’s content with international patent classification (IPC), leveraging bidirectional encoder representations from transformers (BERT), and non-negative matrix factorization (NMF). …”
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A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific Texts by Tsitsi Zengeya, Jean Vincent Fonou Dombeu, Mandlenkosi Gwetu

“…Deep learning approaches, utilizing Bidirectional Encoder Representation from Transformers (BERT) and advanced fine-tuning techniques, have achieved state-of-the-art accuracies in the domain of term extraction from texts. …”
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A Transformer Encoder Approach for Localization Reconstruction During GPS Outages from an IMU and GPS-Based Sensor by Kévin Cédric Guyard, Jonathan Bertolaccini, Stéphane Montavon, Michel Deriaz

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LDAViewer: An Automatic Language-Agnostic System for Discovering State-of-the-Art Topics in Research Using Topic Modeling, Bidirectional Encoder Representations From Transformers,... by Timothy Dillan, Dhomas Hatta Fudholi

“…Subsequently, a numeric document-phrase matrix is created and analyzed using latent Dirichlet allocation (LDA) and bidirectional encoder representations from transformers (BERT) to discover and label topics automatically. …”
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Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

“…We used a robust optimization Bidirectional Encoder Representations from Transformers (BERT) pretraining method to embed these features and constructed a prediction model based on BERT. …”
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Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) by José Ginés Giménez Manuel, José Giner Pérez de Lucia, Marco Antonio Celdrán Bernabeu, José Norberto Mazón López, Juan Carlos Cano Escribá, José María Cecilia Canales

“…In this extended study, we delve deeper into the realm of social sensing by utilising bidirectional encoder representations from transformers (BERT) for topic modelling. …”
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Classifying Aviation Safety Reports: Using Supervised Natural Language Processing (NLP) in an Applied Context by Michael D. New, Ryan J. Wallace

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Domain-Generalized Emotion Recognition on German Text Corpora by Oweys Momenzada, Michael Palk, Stefan Voss

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Short-term cryptocurrency price forecasting based on news headline analysis by Vladimir Dikovitsky

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Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

“…In this paper, we propose a unique approach that utilizes DistilBERT, a distilled version of the Bidirectional Encoder Representations from Transformers, for cancer classification and prediction. …”
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Deep Learning-Based Short Text Summarization: An Integrated BERT and Transformer Encoder–Decoder Approach by Fahd A. Ghanem, M. C. Padma, Hudhaifa M. Abdulwahab, Ramez Alkhatib

“…The proposed approach combines bidirectional encoder representations from transformers (BERT) with a transformer-based encoder–decoder architecture (TEDA), incorporating an attention mechanism to improve contextual understanding. …”
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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach by Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi

“…Results In the post-deployment phase, the URL is encoded using Optimized Bidirectional Encoder Representations from Transformers (OptBERT), after which the features are extracted. …”
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The geometry of meaning: evaluating sentence embeddings from diverse transformer-based models for natural language inference by Mohammed Alsuhaibani

“…Natural language inference (NLI) is a fundamental task in natural language processing that focuses on determining the relationship between pairs of sentences. In this article, we present a simple and straightforward approach to evaluate the effectiveness of various transformer-based models such as bidirectional encoder representations from transformers (BERT), Generative Pre-trained Transformer (GPT), robustly optimized BERT approach (RoBERTa), and XLNet in generating sentence embeddings for NLI. …”
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Leveraging large language models for spelling correction in Turkish by Ceren Guzel Turhan

“…To address this, the research introduces a novel dataset, referred to as NoisyWikiTr, to explore encoder-only models based on bidirectional encoder representations from transformers (BERT) and existing auto-correction tools. …”
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Using a transformer language model to curate a pulmonary embolism dataset from the Medical Information Mart for Intensive Care IV: MIMIC-IV-Ext-PE by Barbara D. Lam, Shengling Ma, Iuliia Kovalenko, Peiqi Wang, Omid Jafari, Ang Li, Steven Horng

“…Using this as our gold standard, we compared the performance of a fine-tuned Bio_ClinicalBERT (bidirectional encoder representations from transformers) transformer language model, known as venous thromboembolism-BERT, with diagnosis codes in the ability to classify reports as PE positive or negative. …”
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Building sustainable information systems and transformer models on demand by Thomas Asselborn, Sylvia Melzer, Simon Schiff, Magnus Bender, Florian Andreas Marwitz, Said Aljoumani, Stefan Thiemann, Konrad Hirschler, Ralf Möller

“…On the one hand, we have achieved a substantial reduction in the development time of an information system, from months to seconds, as well as the ability to fine-tune BERT (Bidirectional Encoder Representations from Transformers) models without specific knowledge in selecting models or tools. …”
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Detecting sarcasm in user-generated content integrating transformers and gated graph neural networks by Zhenkai Qin, Qining Luo, Zhidong Zang, Hongpeng Fu

“…To address this issue, the present study proposes a novel sarcasm detection model that combines bidirectional encoder representations from transformers (BERT) with gated graph neural networks (GGNN), further enhanced by a self-attention mechanism to more effectively capture ironic cues. …”
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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…Subsequently, the Multilingual Bidirectional Encoder Representations from Transformers (mBERT) model was optimized and trained for multiclass sentiment analysis on the code-mixed data. …”
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Trajectory-Ordered Objectives for Self-Supervised Representation Learning of Temporal Healthcare Data Using Transformers: Model Development and Evaluation Study by Ali Amirahmadi, Farzaneh Etminani, Jonas Björk, Olle Melander, Mattias Ohlsson

“…MethodsWe introduce Trajectory Order Objective BERT (Bidirectional Encoder Representations from Transformers; TOO-BERT), a transformer-based model that advances the MLM pretraining approach by integrating a novel TOO to better learn the complex sequential dependencies between medical events. …”
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