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Found 7 papers, 0 papers with code
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
In addressing the computational and memory demands of fine-tuning Large Language Models(LLMs), we propose LoRA-SP(Streamlined Partial Parameter Adaptation), a novel approach utilizing randomized half-selective parameter freezing within the Low-Rank Adaptation(LoRA)framework.
Enhancing Credit Card Fraud Detection A Neural Network and SMOTE Integrated Approach
Credit card fraud detection is a critical challenge in the financial sector, demanding sophisticated approaches to accurately identify fraudulent transactions.
Deep Learning Approaches for Improving Question Answering Systems in Hepatocellular Carcinoma Research
In recent years, advancements in natural language processing (NLP) have been fueled by deep learning techniques, particularly through the utilization of powerful computing resources like GPUs and TPUs.
Text Understanding and Generation Using Transformer Models for Intelligent E-commerce Recommendations
With the rapid development of artificial intelligence technology, Transformer structural pre-training model has become an important tool for large language model (LLM) tasks.
Machine Learning-Based Vehicle Intention Trajectory Recognition and Prediction for Autonomous Driving
This paper introduces a deep learning-based prediction method for autonomous driving lane change behavior, aiming to facilitate safe lane changes and thereby improve road safety.
Utilizing GANs for Fraud Detection: Model Training with Synthetic Transaction Data
Anomaly detection is a critical challenge across various research domains, aiming to identify instances that deviate from normal data distributions.
Utilizing Deep Learning for Enhancing Network Resilience in Finance
In the age of the Internet, people's lives are increasingly dependent on today's network technology.
