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Found 11 papers, 2 papers with code
Physics-Inspired Distributed Radio Map Estimation
While existing deep learning based methods conduct RME given spectrum measurements gathered from dispersed sensors in the region of interest, they rely on centralized data at a fusion center, which however raises critical concerns on data privacy leakages and high communication overloads.
Multi-Aggregator Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-Video Recommendation
Micro-video recommendation is attracting global attention and becoming a popular daily service for people of all ages.
Quantum Cognition-Inspired EEG-based Recommendation via Graph Neural Networks
Current recommendation systems recommend goods by considering users' historical behaviors, social relations, ratings, and other multi-modals.
ER2Score: LLM-based Explainable and Customizable Metric for Assessing Radiology Reports with Reward-Control Loss
Leveraging GPT-4, we designed an easy-to-use data generation pipeline, enabling us to produce extensive training data based on two distinct scoring systems, each containing reports of varying quality along with corresponding scores.
Spectrum Prediction via Graph Structure Learning
Empowered by the graph structure estimator, graph convolutional networks are fueled to effectively extract the correlations in the frequency domain, followed by gated recurrent unit networks to further extract the temporal correlations of each band.
KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models
Harnessing the robust capabilities of Large Language Models (LLMs) for narrative generation, logical reasoning, and common-sense knowledge integration, this study delves into utilizing LLMs to enhance automated radiology report generation (R2Gen).
MRScore: Evaluating Radiology Report Generation with LLM-based Reward System
This paper introduces MRScore, an automatic evaluation metric tailored for radiology report generation by leveraging Large Language Models (LLMs).
Security Risks Concerns of Generative AI in the IoT
In an era where the Internet of Things (IoT) intersects increasingly with generative Artificial Intelligence (AI), this article scrutinizes the emergent security risks inherent in this integration.
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis
This work conducts an evaluation of GPT-4V's multimodal capability for medical image analysis, with a focus on three representative tasks of radiology report generation, medical visual question answering, and medical visual grounding.
Real-time Interface Control with Motion Gesture Recognition based on Non-contact Capacitive Sensing
Capacitive sensing is a prominent technology that is cost-effective and low power consuming with fast recognition speed compared to existing sensing systems.
Robust Convergence in Federated Learning through Label-wise Clustering
Non-IID dataset and heterogeneous environment of the local clients are regarded as a major issue in Federated Learning (FL), causing a downturn in the convergence without achieving satisfactory performance.
