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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 7026–7050 of 9051 papers

TitleStatusHype
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
A Systematic Survey on Deep Generative Models for Graph Generation—0
Exploring the Evolution of GANs through Quality DiversityCode0
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation—0
Speed and fate diversity tradeoff in nematode's early embryogenesis—0
Sequence Generation with Mixed RepresentationsCode1
Illuminating Mario Scenes in the Latent Space of a Generative Adversarial NetworkCode1
Multi-Emitter MAP-Elites: Improving quality, diversity and convergence speed with heterogeneous sets of emittersCode0
Improving Style-Content Disentanglement in Image-to-Image Translation—0
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement LearningCode1
PathGAN: Local Path Planning with Attentive Generative Adversarial NetworksCode0
KQA Pro: A Dataset with Explicit Compositional Programs for Complex Question Answering over Knowledge BaseCode1
Relay Assisted OFDM with Subcarrier Number Modulation in Multi-Hop Cooperative Networks—0
MO-PaDGAN: Generating Diverse Designs with Multivariate Performance Enhancement—0
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle—0
Benefiting Deep Latent Variable Models via Learning the Prior and Removing Latent Regularization—0
Learning Model-Blind Temporal Denoisers without Ground Truths—0
Learning to Generate Novel Domains for Domain GeneralizationCode1
Coronary Heart Disease Diagnosis Based on Improved Ensemble Learning—0
Relevance Transformer: Generating Concise Code Snippets with Relevance Feedback—0
Ultra-Wideband Antenna with MIMO Diversity for 5G Wireless Communication—0
Unsupervised Paraphrasing via Deep Reinforcement Learning—0
Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks—0
Complex Network Construction for Interactive Image Segmentation using Particle Competition and Cooperation: A New Approach—0
Improving auto-encoder novelty detection using channel attention and entropy minimization—0
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