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Found 13 papers, 1 papers with code
MMREC: LLM Based Multi-Modal Recommender System
This surge in content presents unique challenges for designing effective recommender systems.
Data Imputation using Large Language Model to Accelerate Recommendation System
We evaluate our LLM-based imputation method across various tasks within the recommendation system domain, including single classification, multi-classification, and regression compared to traditional data imputation methods.
Advancing Prompt Recovery in NLP: A Deep Dive into the Integration of Gemma-2b-it and Phi2 Models
Prompt recovery, a crucial task in natural language processing, entails the reconstruction of prompts or instructions that language models use to convert input text into a specific output.
Enhance Image-to-Image Generation with LLaVA Prompt and Negative Prompt
We observe a significant improvement in the visual coherence between the generated and input images compared to traditional methods.
Improved AdaBoost for Virtual Reality Experience Prediction Based on Long Short-Term Memory Network
The confusion matrix for the training set shows a total of 177 correct predictions and 52 incorrect predictions, with an accuracy of 77%, precision of 88%, recall of 77% and f1 score of 82%.
Text Sentiment Analysis and Classification Based on Bidirectional Gated Recurrent Units (GRUs) Model
This paper explores the importance of text sentiment analysis and classification in the field of natural language processing, and proposes a new approach to sentiment analysis and classification based on the bidirectional gated recurrent units (GRUs) model.
A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentation
In the ever-evolving landscape of social network advertising, the volume and accuracy of data play a critical role in the performance of predictive models.
Regional Style and Color Transfer
This paper presents a novel contribution to the field of regional style transfer.
Exploring Diverse Methods in Visual Question Answering
This study explores innovative methods for improving Visual Question Answering (VQA) using Generative Adversarial Networks (GANs), autoencoders, and attention mechanisms.
Optimizing Contrail Detection: A Deep Learning Approach with EfficientNet-b4 Encoding
In the pursuit of environmental sustainability, the aviation industry faces the challenge of minimizing its ecological footprint.
Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networks
This paper explores the application of convolutional neural networks for the purpose of multimodal deception detection.
Confidence Trigger Detection: Accelerating Real-time Tracking-by-detection Systems
Real-time object tracking necessitates a delicate balance between speed and accuracy, a challenge exacerbated by the computational demands of deep learning methods.
Using an Ancillary Neural Network to Capture Weekends and Holidays in an Adjoint Neural Network Architecture for Intelligent Building Management
To achieve these requirements, we propose a novel adjoint neural network architecture for time series prediction that uses an ancillary neural network to capture weekend and holiday information.
