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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 6126–6150 of 9051 papers

TitleStatusHype
Video Storytelling: Textual Summaries for Events—0
View Invariant 3D Human Pose Estimation—0
ViGGO: A Video Game Corpus for Data-To-Text Generation in Open-Domain Conversation—0
Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Visible Light Optical Data Centre Links—0
Vision Transformers in Medical Imaging: A Review—0
Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis—0
Visualizing Temporal Topic Embeddings with a Compass—0
Visualizing the Diversity of Representations Learned by Bayesian Neural Networks—0
Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments—0
VisualLens: Personalization through Visual History—0
Visual Place Recognition for Large-Scale UAV Applications—0
VisualQuest: A Diverse Image Dataset for Evaluating Visual Recognition in LLMs—0
Visual Reasoning with Natural Language—0
Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects—0
VisualToolAgent (VisTA): A Reinforcement Learning Framework for Visual Tool Selection—0
Visual Variational Autoencoder Prompt Tuning—0
VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare—0
ViTOC: Vision Transformer and Object-aware Captioner—0
VizExtract: Automatic Relation Extraction from Data Visualizations—0
VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment—0
VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesis—0
Voice Conversion with Diverse Intonation using Conditional Variational Auto-Encoder—0
Voice EHR: Introducing Multimodal Audio Data for Health—0
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