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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 11511175 of 9051 papers

TitleStatusHype
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
Combating noisy labels by agreement: A joint training method with co-regularizationCode1
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion PredictionCode1
COMETA: A Corpus for Medical Entity Linking in the Social MediaCode1
HomoFormer: Homogenized Transformer for Image Shadow RemovalCode1
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout GenerationCode1
Community Forensics: Using Thousands of Generators to Train Fake Image DetectorsCode1
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph DiffusionCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
CompOFA: Compound Once-For-All Networks for Faster Multi-Platform DeploymentCode1
How Many Topics? Stability Analysis for Topic ModelsCode1
Complex Evolutional Pattern Learning for Temporal Knowledge Graph ReasoningCode1
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence LearningCode1
BoostTree and BoostForest for Ensemble LearningCode1
Functional connectivity ensemble method to enhance BCI performance (FUCONE)Code1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
Adding Seemingly Uninformative Labels Helps in Low Data RegimesCode1
Conditional Image Synthesis With Auxiliary Classifier GANsCode1
GenDexGrasp: Generalizable Dexterous GraspingCode1
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image ModelsCode1
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual ConceptsCode1
Concept-skill Transferability-based Data Selection for Large Vision-Language ModelsCode1
Boosting Human-Object Interaction Detection with Text-to-Image Diffusion ModelCode1
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of ModelsCode1
AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker DetectionCode1
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