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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 1126–1150 of 9051 papers

TitleStatusHype
Maximally Separated Active Learning—0
DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model—0
DreamMix: Decoupling Object Attributes for Enhanced Editability in Customized Image InpaintingCode2
Large-Scale Data-Free Knowledge Distillation for ImageNet via Multi-Resolution Data GenerationCode0
MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content CreationCode0
MAT: Multi-Range Attention Transformer for Efficient Image Super-ResolutionCode1
Comparing Photorealism in Game Engines for Synthetic Maritime Computer Vision Datasets—0
Understanding trade-offs in classifier bias with quality-diversity optimization: an application to talent management—0
Image Generation Diversity Issues and How to Tame ThemCode1
VisualLens: Personalization through Visual History—0
Mixed Degradation Image Restoration via Local Dynamic Optimization and Conditional Embedding—0
PriorPath: Coarse-To-Fine Approach for Controlled De-Novo Pathology Semantic Masks Generation—0
Text-to-Image Synthesis: A Decade Survey—0
Multi-Resolution Generative Modeling of Human Motion from Limited Data—0
Towards Foundation Models for Critical Care Time Series—0
Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh RecoveryCode0
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization—0
LetsTalk: Latent Diffusion Transformer for Talking Video Synthesis—0
An Improved Dung Beetle Optimizer for Random Forest Optimization—0
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea—0
Multi-ToM: Evaluating Multilingual Theory of Mind Capabilities in Large Language Models—0
Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in ThaiCode1
ChemSafetyBench: Benchmarking LLM Safety on Chemistry DomainCode0
AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data GenerationCode2
Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration—0
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