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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 5226–5250 of 9051 papers

TitleStatusHype
Reconfigurable Holographic Surface: A New Paradigm to Implement Holographic Radio—0
Link-level simulator for 5G localizationCode0
Personalized Student Attribute Inference—0
Personalized Prediction of Offensive News Comments by Considering the Characteristics of Commenters—0
Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer—0
Boosting Out-of-Distribution Detection with Multiple Pre-trained ModelsCode0
Recommending on graphs: a comprehensive review from a data perspective—0
Multi-Frequency Channel Modeling for Millimeter Wave and THz Wireless Communication via Generative Adversarial NetworksCode0
Cross-Linguistic Syntactic Difference in Multilingual BERT: How Good is It and How Does It Affect Transfer?Code0
Secure and Privacy Preserving Proxy Biometrics Identities—0
Efficient aggregation of face embeddings for decentralized face recognition deployments (extended version)—0
A Pattern Discovery Approach to Multivariate Time Series Forecasting—0
Unleashing the Power of Visual Prompting At the Pixel LevelCode0
CausalDialogue: Modeling Utterance-level Causality in ConversationsCode0
Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction—0
DimonGen: Diversified Generative Commonsense Reasoning for Explaining Concept RelationshipsCode0
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization—0
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
Natural Language to Code Generation in Interactive Data Science Notebooks—0
Exploring Hybrid and Ensemble Models for Multiclass Prediction of Mental Health Status on Social Media—0
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization—0
PVGRU: Generating Diverse and Relevant Dialogue Responses via Pseudo-Variational Mechanism—0
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political DiscussionCode0
Natural Language Processing in Customer Service: A Systematic Review—0
Experiments on Generalizability of BERTopic on Multi-Domain Short Text—0
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