An LLM driven framework for email spam detection using DistilBERT embeddings and neural classifiers
Email spam detection is still a critical challenge in cybersecurity due to the increasing sophistication of malicious campaigns. Effective filtering is essential to protect users from phishing, fraud, and privacy violations.
G. Pradeep Reddy +4 more
doaj +1 more source
INTENT RECOGNITION USING DISTILBERT AND LANGUAGE MODELS
Intent classification in Natural Language Processing involves identifying the intention of the user based on their input/interaction with an interface. This can be in a natural usage setting (voice assistants) or an interaction between users, customer service personnel, or agents (in a large organization). This paper aims to study the problem of intent
openaire +2 more sources
Fine-tuning DistilBERT for new classification
This thesis presents a study on the development and optimization of a natural language processing (NLP) model for the automatic classification of news according to their thematic categories (politics, sports, entertainment, etc.). The work focuses on the application and evaluation of machine learning techniques based on artificial neural networks, with
openaire +1 more source
AI-Assisted Rapid Quality Analysis in Implementation Science: Methodological Study. [PDF]
Adegbemijo A +4 more
europepmc +1 more source
Online News Sentiment Classification Using DistilBERT
Samuel Kofi Akpatsa +6 more
openaire +1 more source
Transformer-based classification and interpretability of NR3C1 expression patterns in OSCC: Metabolic adaptation insights. [PDF]
Yuwanati M, Yadalam PK, Mullainathan S.
europepmc +1 more source
A hybrid stacked ensemble learning framework for multilabel text emotion detection. [PDF]
Adamu H, Azmi Murad MA, Nasharuddin NA.
europepmc +1 more source
Efficient detection of AI-generated scientific abstracts with a lightweight transformer. [PDF]
Zhang C, Zhou W.
europepmc +1 more source
Identifying Patient Sentiment in Atopic Dermatitis Treatment: Large Language Model Approach. [PDF]
Cummins JA, Yu J.
europepmc +1 more source
Federated learning-powered real-time behavioral intrusion detection leveraging LSTM, attention, GANs, and large language models. [PDF]
AlHayan A, Al-Muhtadi J.
europepmc +1 more source

