SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4876–4900 of 9051 papers

TitleStatusHype
Improving Computed Tomography (CT) Reconstruction via 3D Shape InductionCode0
Tunable Hybrid Proposal Networks for the Open World—0
Towards Confidence-aware Calibrated Recommendation—0
Do diverse and inclusive workplaces benefit investors? An Empirical Analysis on Europe and the United States—0
Automated Pruning of Polyculture Plants—0
An Entropy-based Measure of Intelligence Degree of System Structures—0
CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval—0
Self-Supervised Place Recognition by Refining Temporal and Featural Pseudo Labels from Panoramic DataCode1
Text to Image Generation: Leaving no Language Behind—0
Diverse Video Captioning by Adaptive Spatio-temporal AttentionCode0
Adaptive Pulse Compression for Sidelobes Reduction in Stretch Processing based MIMO Radars—0
Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIVCode1
Enhancing Targeted Attack Transferability via Diversified Weight Pruning—0
VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social MediaCode1
Coherent Visual Storytelling via Parallel Top-Down Visual and Topic Attention—0
Quality Diversity Evolutionary Learning of Decision Trees—0
Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork—0
Road detection via a dual-task network based on cross-layer graph fusion modules—0
TRoVE: Transforming Road Scene Datasets into Photorealistic Virtual EnvironmentsCode1
PoseTrans: A Simple Yet Effective Pose Transformation Augmentation for Human Pose EstimationCode1
A User-Centered Investigation of Personal Music Tours—0
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding—0
Combining Predictions under Uncertainty: The Case of Random Decision TreesCode0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
A Case for Rejection in Low Resource ML DeploymentCode1
Show:102550
← PrevPage 196 of 363Next →

No leaderboard results yet.