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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
Chain-of-Choice Hierarchical Policy Learning for Conversational RecommendationCode1
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial TrajectoryCode1
Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose EstimationCode1
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive TestingCode1
Goals as Reward-Producing ProgramsCode1
BoostTree and BoostForest for Ensemble LearningCode1
GLAMOUR: Graph Learning over Macromolecule RepresentationsCode1
GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection MethodCode1
Graph Meta Network for Multi-Behavior RecommendationCode1
FS6D: Few-Shot 6D Pose Estimation of Novel ObjectsCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
CityPersons: A Diverse Dataset for Pedestrian DetectionCode1
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series ForecastingCode1
Class-Aware Mask-Guided Feature Refinement for Scene Text RecognitionCode1
Boosting Human-Object Interaction Detection with Text-to-Image Diffusion ModelCode1
Adaptively Sparse TransformersCode1
CLIP-VG: Self-paced Curriculum Adapting of CLIP for Visual GroundingCode1
Clotho: An Audio Captioning DatasetCode1
CLoG: Benchmarking Continual Learning of Image Generation ModelsCode1
Group-wise Inhibition based Feature Regularization for Robust ClassificationCode1
Frequency Domain Model Augmentation for Adversarial AttackCode1
Fractal Autoencoders for Feature SelectionCode1
A View From Somewhere: Human-Centric Face RepresentationsCode1
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
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