SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8601–8625 of 9051 papers

TitleStatusHype
Diversity-Aware Sign Language Production through a Pose Encoding Variational Autoencoder—0
Diversity-aware social robots meet people: beyond context-aware embodied AI—0
DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling—0
Diversity-aware Web APIs Recommendation with Compatibility Guarantee—0
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification—0
Voice EHR: Introducing Multimodal Audio Data for Health—0
Diversity-based Design Assist for Large Legged Robots—0
Diversity Based Edge Pruning of Neural Networks Using Determinantal Point Processes—0
Voice of a Continent: Mapping Africa's Speech Technology Frontier—0
Diversity-Based Recruitment in Crowdsensing By Combinatorial Multi-Armed Bandits—0
Composable Core-sets for Diversity Approximation on Multi-Dataset Streams—0
Diversity Boosted Learning for Domain Generalization with Large Number of Domains—0
A Diversity-Aware Domain Development Methodology—0
A Diverse Clustering Particle Swarm Optimizer for Dynamic Environment: To Locate and Track Multiple Optima—0
Diversity by Phonetics and its Application in Neural Machine Translation—0
Diversity Covariance-Aware Prompt Learning for Vision-Language Models—0
Diversity, Density, and Homogeneity: Quantitative Characteristic Metrics for Text Collections—0
A Distributed Local Energy Market Clearing Framework Using a Two-Loop ADMM Method—0
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning—0
Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder—0
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning—0
A Discrete CVAE for Response Generation on Short-Text Conversation—0
Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memory—0
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Diversity driven Query Rewriting in Search Advertising—0
Show:102550
← PrevPage 345 of 363Next →

No leaderboard results yet.