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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 1076–1100 of 9051 papers

TitleStatusHype
Continual Object Detection via Prototypical Task Correlation Guided Gating MechanismCode1
Adaptively Sparse TransformersCode1
Continual Variational Autoencoder Learning via Online Cooperative MemorizationCode1
Contrastive Syn-to-Real GeneralizationCode1
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text GenerationCode1
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide GenerationCode1
Controllable Group Choreography using Contrastive DiffusionCode1
Controllable Text Generation via Probability Density Estimation in the Latent SpaceCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
Bacteriophage classification for assembled contigs using Graph Convolutional NetworkCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT ImagesCode1
BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal TransferCode1
Cross-Covariate Gait Recognition: A BenchmarkCode1
Cross-Domain Feature Augmentation for Domain GeneralizationCode1
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised SegmentationCode1
Context-Transformer: Tackling Object Confusion for Few-Shot DetectionCode1
Curriculum-guided Hindsight Experience ReplayCode1
Content-aware Tile Generation using Exterior Boundary InpaintingCode1
dacl10k: Benchmark for Semantic Bridge Damage SegmentationCode1
Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text GenerationCode1
Contextual Diversity for Active LearningCode1
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