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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 4951–5000 of 9051 papers

TitleStatusHype
Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning—0
Learning Object Placement via Dual-path Graph CompletionCode1
Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness—0
Few-shot Image Generation Using Discrete Content Representation—0
Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly DetectionCode1
BigIssue: A Realistic Bug Localization Benchmark—0
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific DeltaCode1
Omni3D: A Large Benchmark and Model for 3D Object Detection in the WildCode2
Pretraining a Neural Network before Knowing Its ArchitectureCode2
Continual Variational Autoencoder Learning via Online Cooperative MemorizationCode1
FaceFormer: Scale-aware Blind Face Restoration with Transformers—0
Controllable and Guided Face Synthesis for Unconstrained Face RecognitionCode1
Difficulty-Aware Simulator for Open Set RecognitionCode1
Large Scale Radio Frequency Signal ClassificationCode2
DH-AUG: DH Forward Kinematics Model Driven Augmentation for 3D Human Pose EstimationCode1
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANsCode1
Towards Diverse and Faithful One-shot Adaption of Generative Adversarial NetworksCode1
Unsupervised Medical Image Translation with Adversarial Diffusion ModelsCode2
GANzilla: User-Driven Direction Discovery in Generative Adversarial Networks—0
Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary SpaceCode1
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution DetectionCode0
Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model—0
D-CBRS: Accounting For Intra-Class Diversity in Continual Learning—0
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index—0
Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text GenerationCode1
Diversity-aware social robots meet people: beyond context-aware embodied AI—0
Causal Conceptions of Fairness and their Consequences—0
IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-trainingCode0
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy OptimizationCode1
Frequency Domain Model Augmentation for Adversarial AttackCode1
Origin of power laws and their spatial fractal structure for city-size distributions—0
Interference-Limited Ultra-Reliable and Low-Latency Communications: Graph Neural Networks or Stochastic Geometry?—0
Fine-grained Activities of People Worldwide—0
Multimodal Multi-objective Optimization: Comparative Study of the State-of-the-ArtCode1
SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder—0
Learning an evolved mixture model for task-free continual learning—0
Interaction Pattern Disentangling for Multi-Agent Reinforcement LearningCode1
PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learning—0
Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution StrategiesCode0
Learning to Diversify for Product Question Generation—0
Mitigating shortage of labeled data using clustering-based active learning with diversity explorationCode0
Quantitative Assessment of DESIS Hyperspectral Data for Plant Biodiversity Estimation in Australia—0
DBN-Mix: Training Dual Branch Network Using Bilateral Mixup Augmentation for Long-Tailed Visual Recognition—0
PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch—0
Vision-and-Language PretrainingCode0
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
T-DominO: Exploring Multiple Criteria with Quality-Diversity and the Tournament Dominance ObjectiveCode0
Recommendation Systems with Distribution-Free Reliability Guarantees—0
Anomaly-aware multiple instance learning for rare anemia disorder classificationCode0
Selectively increasing the diversity of GAN-generated samples—0
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