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Found 10 papers, 3 papers with code
SPICED: News Similarity Detection Dataset with Multiple Topics and Complexity Levels
Nowadays, the use of intelligent systems to detect redundant information in news articles has become especially prevalent with the proliferation of news media outlets in order to enhance user experience.
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems
Federated Learning (FL) has emerged as a key approach for distributed machine learning, enhancing online personalization while ensuring user data privacy.
MM-GEF: Multi-modal representation meet collaborative filtering
In modern e-commerce, item content features in various modalities offer accurate yet comprehensive information to recommender systems.
STA: Self-controlled Text Augmentation for Improving Text Classifications
Despite recent advancements in Machine Learning, many tasks still involve working in low-data regimes which can make solving natural language problems difficult.
Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation
This approach helps to mitigate the negative knowledge transfer problem from multiple domains and improve overall representation.
Topics as Entity Clusters: Entity-based Topics from Language Models and Graph Neural Networks
We demonstrate that our approach consistently outperforms other state-of-the-art topic models across coherency metrics and find that the explicit knowledge encoded in the graph-based embeddings provides more coherent topics than the implicit knowledge encoded with the contextualized embeddings of language models.
Multilingual News Location Detection using an Entity-Based Siamese Network with Semi-Supervised Contrastive Learning and Knowledge Base
To evaluate the effectiveness of our approach, and due to the lack of datasets in this area, we also contribute to the research community with a gold-standard multilingual news-location dataset, NewsLOC.
Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors
The proliferation of DeepFake technology is a rising challenge in today's society, owing to more powerful and accessible generation methods.
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction
In Federated Learning (FL) of click-through rate (CTR) prediction, users' data is not shared for privacy protection.
Matching Demand with Supply in the Smart Grid using Agent-Based Multiunit Auction
Recent work has suggested reducing electricity generation cost by cutting the peak to average ratio (PAR) without reducing the total amount of the loads.
