Results 21 to 30 of about 1,082 (177)

Hybrid CNN-DistilBERT and CNN-DistilBERT-SVM architectures for multimodal sentiment analysis on speech and text data [PDF]

EPJ Web of Conferences
The task of sentiment analysis in human speech (acoustic and textual) is crucial for the development of empathic artificial intelligence systems in the fields of human-computer interaction (HCI) and affective computing.
Benzirar Abdelkader, Boulal Hossam, Bouami Mouncef Filali, Hamidi Mohamed   +3 more
doaj   +1 more source

DistilBERT-based Argumentation Retrieval for Answering Comparative Questions. [PDF]

, 2021
In the current world, individuals are faced with decision making problems and opinion formation processes on a daily basis. For example, debating or choosing between two similar products. However, answering a comparative question by retrieving documents based only on traditional measures (such as TF-IDF and BM25) does not always satisfy the need. Thus,
Alhamzeh, Alaa, Bouhaouel, Mohamed, Egyed-Zsigmond, Előd, Mitrović, Jelena   +3 more
openaire   +2 more sources

Automatic rating of therapist facilitative interpersonal skills in text: A natural language processing application

Frontiers in Digital Health, 2022
BackgroundWhile message-based therapy has been shown to be effective in treating a range of mood disorders, it is critical to ensure that providers are meeting a consistently high standard of care over this medium.
James M. Zech, James M. Zech, Robert Steele, Robert Steele, Victoria K. Foley, Thomas D. Hull   +5 more
doaj   +1 more source

Few-Shot Learning for Classifying Genuine and Bot Comments on YouTube Using Transformer Models

Journal of Applied Informatics and Computing
This study aims to develop a comment classification system on the YouTube platform to distinguish between real accounts and bot accounts, addressing the challenge of limited labeled data through a few-shot learning approach.
Nahdah Fikriah Nst, Defry Hamdhana, Mukti Qamal   +2 more
doaj   +1 more source

Multi-Class News Classification with BERT, DistilBERT, RoBERTa, and ELECTRA Natural Language Processing Models

Düzce Üniversitesi Bilim ve Teknoloji Dergisi
The rapid proliferation of digital news sources today necessitates the effective analysis and classification of large-scale textual data. In this study, BERT (Bidirectional Encoder Representations from Transformers) and its derivatives — DistilBERT ...
Ahmet Albayrak, Serdar Arpacı, Arafat Şentürk   +2 more
doaj   +1 more source

Comparison of Online Gambling Promotion Detection Performance Using DistilBERT and DeBERTa Models

Journal of Applied Informatics and Computing
Online gambling promotions on social media have become a serious concern in Indonesia, where perpetrators use ambiguous and disguised language to evade detection. This study compares two transformer-based models, DistilBERT and DeBERTa, in detecting such
Halim Meliana Pratama, IGN Lanang Wijayakusuma, Ratna Sari Widiastuti   +2 more
doaj   +1 more source

Baselining Large Language Model Performance in Systems Engineering Using SysEngBench

Systems Engineering, EarlyView.
ABSTRACT In the rapidly evolving field of artificial intelligence (AI), large language model s (LLMs) have demonstrated impressive capabilities in generating natural language. However, their proficiency in specialized domains, particularly in the field of systems engineering (SE), remains less explored and unquantified.
Ryan Bell, Ryan Longshore, Raymond Madachy, Ashlyn Hanrahan   +3 more
wiley   +1 more source

Transformer‐Based Contextual Modeling for Predicting Calories From Recipes

Applied AI Letters, Volume 7, Issue 3, October 2026.
A transformer‐based regression model with token‐level attention pooling is proposed for predicting calorie content directly from unstructured recipe text. By fine‐tuning RoBERTa in an end‐to‐end manner, attention is learned to be focused on calorie‐relevant tokens such as ingredients, fats, and cooking methods.
Md. Siam Ansary, Amina Brinto
wiley   +1 more source

Small Language Models: A Systematic Review of Computational Trade‐Offs, Privacy Advantages and Deployment in Intelligent Systems

Expert Systems, Volume 43, Issue 8, August 2026.
ABSTRACT This systematic review synthesizes evidence from 68 studies, including peer‐reviewed journal articles, indexed conference/workshop proceedings and five remaining arXiv preprints published between 2022 and 2025, on small language models (SLMs) as computationally efficient alternatives to large language models (LLMs).
Sena Dikici, Turgay Tugay Bilgin
wiley   +1 more source

Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models

Радіоелектронні і комп'ютерні системи
This study investigates the implementation of different sentiment analysis models, exploring their theoretical foundations, robust evaluation criteria, and significant findings, and integrating natural language processing methods to preprocess data ...
Chaimaa Benyamani, Hassan Badi, Imad Badi, Aziz Khamjane   +3 more
doaj   +1 more source