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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 28762900 of 9051 papers

TitleStatusHype
Exploring the Role of Node Diversity in Directed Graph Representation LearningCode0
CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and CalibrationCode0
Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic SegmentationCode0
Exploring the Performance-Reproducibility Trade-off in Quality-DiversityCode0
Exploring the Role of Diversity in Example Selection for In-Context LearningCode0
Cats or CAT scans: transfer learning from natural or medical image source datasets?Code0
New Metrics to Encourage Innovation and Diversity in Information Retrieval ApproachesCode0
Fair Summarization: Bridging Quality and Diversity in Extractive SummariesCode0
DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant RecommendationsCode0
Exploring Sparsity for Parameter Efficient Fine Tuning Using WaveletsCode0
Deep Hashing with Category Mask for Fast Video RetrievalCode0
Exploring the Capabilities of Large Language Models for Generating Diverse Design SolutionsCode0
Exploring Precision and Recall to assess the quality and diversity of LLMsCode0
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class AnnealingCode0
Exploring Model Consensus to Generate Translation ParaphrasesCode0
Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution StrategiesCode0
DPPy: Sampling DPPs with PythonCode0
Nondeterminism and Instability in Neural Network OptimizationCode0
Exploring Model Learning Heterogeneity for Boosting Ensemble RobustnessCode0
Exploring the Evolution of GANs through Quality DiversityCode0
Exploring Diversity in Back Translation for Low-Resource Machine TranslationCode0
Contributions of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO VarianceCode0
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
Exploring Flat Minima for Domain Generalization with Large Learning RatesCode0
Bags of Projected Nearest Neighbours: Competitors to Random Forests?Code0
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