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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 2676–2700 of 9051 papers

TitleStatusHype
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Describing like humans: on diversity in image captioningCode0
Learning Diverse Features in Vision Transformers for Improved GeneralizationCode0
Beer Organoleptic Optimisation: Utilising Swarm Intelligence and Evolutionary Computation MethodsCode0
Learning Diversified Feature Representations for Facial Expression Recognition in the WildCode0
Few-Shot Specific Emitter Identification via Hybrid Data Augmentation and Deep Metric LearningCode0
Diversity Augmented Conditional Generative Adversarial Network for Enhanced Multimodal Image-to-Image TranslationCode0
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAGCode0
Fine-Grained Detoxification via Instance-Level Prefixes for Large Language ModelsCode0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
BEE: Metric-Adapted Explanations via Baseline Exploration-ExploitationCode0
DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology DiagnosisCode0
Analysis of the first Genetic Engineering Attribution ChallengeCode0
Few-shot Personalization of LLMs with Mis-aligned ResponsesCode0
Few-shot Image Generation with Diffusion ModelsCode0
Few-shot Image Generation via Masked DiscriminationCode0
Diversity in deep generative models and generative AICode0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Federated Neural Topic ModelsCode0
Federated Stain Normalization for Computational PathologyCode0
Feature Space Particle Inference for Neural Network EnsemblesCode0
FedCCRL: Federated Domain Generalization with Cross-Client Representation LearningCode0
Diversity Aware Relevance Learning for Argument SearchCode0
Federated Visual Classification with Real-World Data DistributionCode0
Few-shot Quality-Diversity OptimizationCode0
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