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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 826–850 of 9051 papers

TitleStatusHype
Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackersCode1
BiRT: Bio-inspired Replay in Vision Transformers for Continual LearningCode1
Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized DiversityCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent LearningCode1
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingCode1
DiffuSum: Generation Enhanced Extractive Summarization with DiffusionCode1
Class-Balancing Diffusion ModelsCode1
Generating images of rare concepts using pre-trained diffusion modelsCode1
DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion modelsCode1
Effect of latent space distribution on the segmentation of images with multiple annotationsCode1
You Never Get a Second Chance To Make a Good First Impression: Seeding Active Learning for 3D Semantic SegmentationCode1
Revisiting k-NN for Fine-tuning Pre-trained Language ModelsCode1
Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric ViewsCode1
NoisyTwins: Class-Consistent and Diverse Image Generation through StyleGANsCode1
Shape-Erased Feature Learning for Visible-Infrared Person Re-IdentificationCode1
Zero-shot Generative Model Adaptation via Image-specific Prompt LearningCode1
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen DomainsCode1
Industrial Anomaly Detection with Domain Shift: A Real-world Dataset and Masked Multi-scale ReconstructionCode1
Efficient OCR for Building a Diverse Digital HistoryCode1
SLPerf: a Unified Framework for Benchmarking Split LearningCode1
DivClust: Controlling Diversity in Deep ClusteringCode1
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking TasksCode1
The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web ArchivesCode1
A View From Somewhere: Human-Centric Face RepresentationsCode1
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