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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 9026–9050 of 9051 papers

TitleStatusHype
Establishing a Unified Evaluation Framework for Human Motion Generation: A Comparative Analysis of MetricsCode0
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding DatasetsCode0
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical SpaceCode0
Brain Tumor Synthetic Data Generation with Adaptive StyleGANsCode0
Error Diversity Matters: An Error-Resistant Ensemble Method for Unsupervised Dependency ParsingCode0
Augmented Shortcuts for Vision TransformersCode0
Instrumental Variable Estimation for Compositional TreatmentsCode0
EquiBoost: An Equivariant Boosting Approach to Molecular Conformation GenerationCode0
Analyzing the Habitable Zones of Circumbinary Planets Using Machine LearningCode0
Open-Source Morphology for Endangered Mordvinic LanguagesCode0
E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender SystemsCode0
Syntactic and Semantic-driven Learning for Open Information ExtractionCode0
Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and BeyondCode0
EPiC: Ensemble of Partial Point Clouds for Robust ClassificationCode0
EnsLM: Ensemble Language Model for Data Diversity by Semantic ClusteringCode0
Syntax Customized Video Captioning by Imitating Exemplar SentencesCode0
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer LearningCode0
Toward Multimodal Image-to-Image TranslationCode0
Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering SystemsCode0
Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational CostsCode0
Using Coreference Links to Improve Spanish-to-English Machine TranslationCode0
Dataset Geography: Mapping Language Data to Language UsersCode0
Dataset for the First Evaluation on Chinese Machine Reading ComprehensionCode0
OptAGAN: Entropy-based finetuning on text VAE-GANCode0
Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPUCode0
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