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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 5126–5150 of 9051 papers

TitleStatusHype
GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language ModelsCode1
Symptom Identification for Interpretable Detection of Multiple Mental Disorders—0
Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining DatasetsCode0
User Clustering for Rate Splitting using Machine Learning—0
Looking for a Handsome Carpenter! Debiasing GPT-3 Job AdvertisementsCode0
Diversity Enhanced Table-to-Text Generation via Type Control—0
AFEC: A Knowledge Graph Capturing Social Intelligence in Casual Conversations—0
Covariance Matrix Adaptation MAP-Annealing—0
Diversity Preference-Aware Link Recommendation for Online Social Networks—0
Unsupervised Sign Language Phoneme Clustering using HamNoSys Notation—0
UCC: Uncertainty guided Cross-head Co-training for Semi-Supervised Semantic SegmentationCode1
KERPLE: Kernelized Relative Positional Embedding for Length ExtrapolationCode1
StyLitGAN: Prompting StyleGAN to Produce New Illumination Conditions—0
Diversity vs. Recognizability: Human-like generalization in one-shot generative modelsCode0
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble—0
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?—0
Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection—0
Diverse Weight Averaging for Out-of-Distribution GeneralizationCode1
Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational BayesCode0
Simple Regularisation for Uncertainty-Aware Knowledge Distillation—0
GPoeT-2: A GPT-2 Based Poem GeneratorCode0
Pluralistic Image Completion with Probabilistic Mixture-of-Experts—0
RandoMix: A mixed sample data augmentation method with multiple mixed modes—0
Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification—0
Many Field Packet Classification with Decomposition and Reinforcement Learning—0
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