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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

Showing 80268050 of 9051 papers

TitleStatusHype
BEE: Metric-Adapted Explanations via Baseline Exploration-ExploitationCode0
Result Diversification in Search and Recommendation: A SurveyCode0
Contributions of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO VarianceCode0
LLaVA-VSD: Large Language-and-Vision Assistant for Visual Spatial DescriptionCode0
Hierarchical Pruning of Deep Ensembles with Focal DiversityCode0
LLM-based multi-agent poetry generation in non-cooperative environmentsCode0
DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant RecommendationsCode0
Practice Makes a Solver Perfect: Data Augmentation for Math Word Problem SolversCode0
A Survey of Data Synthesis ApproachesCode0
LLMs for Extremely Low-Resource Finno-Ugric LanguagesCode0
Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data DiversityCode0
VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPSCode0
Towards Hate Speech Detection at Large via Deep Generative ModelingCode0
DOS: Diverse Outlier Sampling for Out-of-Distribution DetectionCode0
LLM-TOPLA: Efficient LLM Ensemble by Maximising DiversityCode0
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic SystemsCode0
Variability in the local and global composition of human T-cell receptor repertoires during thymic development across cell types and individualsCode0
LMEraser: Large Model Unlearning through Adaptive Prompt TuningCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
Hierarchical Federated Learning in Multi-hop Cluster-Based VANETsCode0
Show, Control and Tell: A Framework for Generating Controllable and Grounded CaptionsCode0
Predicting Complete 3D Models of Indoor ScenesCode0
Consistency-based anomaly detection with adaptive multiple-hypotheses predictionsCode0
Siamese Graph Learning for Semi-supervised Age EstimationCode0
Local Diversity of Condorcet DomainsCode0
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