Results 71 to 80 of about 5,471 (199)

An Improved Transformer‐Based Model for Drone Forensic Analysis

Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.
In recent years, drones have become ubiquitous across various industries, raising concerns about their potential malfunctions. Investigating such malfunctions requires effective forensic analysis techniques. The purpose of this research is to enhance Transformer architecture to address the specific challenge of analyzing drone malfunctions using log ...
Arda Surya Editya, Tohari Ahmad, Hudan Studiawan, Pramita Mishra   +3 more
wiley   +1 more source

GraLMatch : matching groups of entities with graphs and language models [PDF]

In this paper, we present an end-to-end multi-source Entity Matching problem, which we call entity group matching, where the goal is to assign to the same group records originating from multiple data sources but representing the same real-world entity ...
Braschler, Martin, de Meer Pardo, Fernando, Gehrig, Dennis, Hadji Misheva, Branka, Lehmann, Claude, Nagy, Andrea, Nicoli, Stefano, Stockinger, Kurt   +7 more
core   +1 more source

Detection of Biased Phrases in the Wiki Neutrality Corpus for Fairer Digital Content Management Using Artificial Intelligence

Big Data and Cognitive Computing
Detecting biased language in large-scale corpora, such as the Wiki Neutrality Corpus, is essential for promoting neutrality in digital content. This study systematically evaluates a range of machine learning (ML) and deep learning (DL) models for the ...
Abdullah, Muhammad Ateeb Ather, Olga Kolesnikova, Grigori Sidorov   +3 more
doaj   +1 more source

Natural Language Processing for Aviation Safety: Predicting Injury Levels from Incident Reports in Australia

Modelling
This study investigates the application of advanced deep learning models for the classification of aviation safety incidents, focusing on four models: Simple Recurrent Neural Network (sRNN), Gated Recurrent Unit (GRU), Bidirectional Long Short-Term ...
Aziida Nanyonga, Keith Joiner, Ugur Turhan, Graham Wild   +3 more
doaj   +1 more source

Large Language Models for Detecting Cyberattacks on Smart Grid Protective Relays

IEEE Open Access Journal of Power and Energy
This paper presents a large language model (LLM)–based framework that adapts and fine-tunes compact LLMs for detecting cyberattacks on transformer current differential relays (TCDRs), which can otherwise cause false tripping of critical power ...
Ahmad Mohammad Saber, Saeed Jafari, Zhengmao Ouyang, Paul Budnarain, Amr Youssef, Deepa Kundur   +5 more
doaj   +1 more source

Fractal Self-Similarity in Semantic Convergence: Gradient of Embedding Similarity across Transformer Layers

Fractal and Fractional
This paper presents a mathematical analysis of semantic convergence in transformer-based language models, drawing inspiration from the concept of fractal self-similarity.
Minhyeok Lee
doaj   +1 more source

Dementia Prediction Using Hierarchical Attention and Evaluation of Context Quality [PDF]

Alzheimers Dement
Abstract Background A clinical interview is the first step in diagnosing dementia, as it helps determine whether the patient needs further evaluation. Large Language Models (LLMs) excel in understanding textual contexts and show significant promise in various domains, but their performance on real medical records has been less explored.
Lee K, Lim S, Lee I, Kim O, Jung H, Kim S, Kim H, Kang K, Lee J.   +8 more
europepmc   +2 more sources

DETECTING DEPRESSION IN TWEETS USING DISTILBERT

International Journal of Innovative Research in Computer Science & Technology, 2021
U. Yasaswini ., Y. Sasidhar ., P. Siva Sai ., P. Eswar ., V. Swathi .   +4 more
openaire   +1 more source

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

CoRR, 2019
February 2020 - Revision: fix bug in evaluation metrics, updated metrics, argumentation unchanged. 5 pages, 1 figure, 4 tables.
Victor Sanh, Lysandre Debut, Julien Chaumond, Thomas Wolf 0008   +3 more
openaire   +2 more sources

From text to code – Leveraging machine learning for neurology outpatient clinical codingBox 1. Prompt engineering template used in calls to Mistral 7B. was replaced with each processed clinic letter body (the complete prompt is available in Appendix 4).Box 2. Example of hallucination using Mistral 7b model

Neuroscience Informatics
Background: Most neurological care is delivered in outpatient settings without mandated clinical coding. The clinical records remain stored as unstructured text with inconsistent formatting.
Elena Purcaru, Michael George, Matthew Stammers, Christopher Kipps   +3 more
doaj   +1 more source