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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 1151–1200 of 9051 papers

TitleStatusHype
Generating Diverse 3D Reconstructions from a Single Occluded Face ImageCode1
Generating Object StampsCode1
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion PredictionCode1
Contrastive Losses Are Natural Criteria for Unsupervised Video SummarizationCode1
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load ForecastingCode1
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence LearningCode1
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic SegmentationCode1
Human-M3: A Multi-view Multi-modal Dataset for 3D Human Pose Estimation in Outdoor ScenesCode1
HUMOS: Human Motion Model Conditioned on Body ShapeCode1
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
ID-Booth: Identity-consistent Face Generation with Diffusion ModelsCode1
IDM: An Intermediate Domain Module for Domain Adaptive Person Re-IDCode1
Building a Conversational Agent Overnight with Dialogue Self-PlayCode1
Conditioned Query Generation for Task-Oriented Dialogue SystemsCode1
Image Generation From Small Datasets via Batch Statistics AdaptationCode1
Conditional Sound Generation Using Neural Discrete Time-Frequency Representation LearningCode1
Conditioned Text Generation with Transfer for Closed-Domain Dialogue SystemsCode1
Considering user agreement in learning to predict the aesthetic qualityCode1
Adaptively Sparse TransformersCode1
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of ModelsCode1
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid MotionsCode1
Generalized Probabilistic U-Net for medical image segementationCode1
Can 3D Vision-Language Models Truly Understand Natural Language?Code1
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural NetworksCode1
Contextual Diversity for Active LearningCode1
Context-Transformer: Tackling Object Confusion for Few-Shot DetectionCode1
Continual Learning for Image Segmentation with Dynamic QueryCode1
BenthicNet: A global compilation of seafloor images for deep learning applicationsCode1
GenDexGrasp: Generalizable Dexterous GraspingCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Contrastive Syn-to-Real GeneralizationCode1
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text GenerationCode1
A View From Somewhere: Human-Centric Face RepresentationsCode1
Controllable Group Choreography using Contrastive DiffusionCode1
Inversion Circle Interpolation: Diffusion-based Image Augmentation for Data-scarce ClassificationCode1
Improving Diversity with Adversarially Learned Transformations for Domain GeneralizationCode1
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot FillingCode1
General and Task-Oriented Video SegmentationCode1
Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human ProgrammersCode1
Generating Smooth Pose Sequences for Diverse Human Motion PredictionCode1
Bootstrapping Referring Multi-Object TrackingCode1
Controlling Behavioral Diversity in Multi-Agent Reinforcement LearningCode1
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion ModelsCode1
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet AccuracyCode1
AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker DetectionCode1
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