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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 1801–1825 of 9051 papers

TitleStatusHype
Coherent FDA Radar: Transmitter and Receiver Design and Analysis—0
Contrastive Learning for Image Complexity Representation—0
Diverse Generation while Maintaining Semantic Coordination: A Diffusion-Based Data Augmentation Method for Object Detection—0
FDA Jamming Against Airborne Phased-MIMO Radar-Part I: Matched Filtering and Spatial Filtering—0
Cross Pseudo Supervision Framework for Sparsely Labelled Geospatial Images—0
Low-Cost Self-Ensembles Based on Multi-Branch Transformation and Grouped ConvolutionCode0
Spin glass model of in-context learning—0
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and CostCode0
COM Kitchens: An Unedited Overhead-view Video Dataset as a Vision-Language BenchmarkCode1
ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative GenerationCode1
Effective Demonstration Annotation for In-Context Learning via Language Model-Based Determinantal Point Process—0
LDFaceNet: Latent Diffusion-based Network for High-Fidelity Deepfake Generation—0
Why Perturbing Symbolic Music is Necessary: Fitting the Distribution of Never-used Notes through a Joint Probabilistic Diffusion Model—0
Scene-wise Adaptive Network for Dynamic Cold-start Scenes Optimization in CTR PredictionCode0
Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2Code3
GLDiTalker: Speech-Driven 3D Facial Animation with Graph Latent Diffusion Transformer—0
DebateQA: Evaluating Question Answering on Debatable KnowledgeCode1
FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only—0
Tailoring Graph Neural Network-based Flow-guided Localization to Individual Bloodstreams and Activities—0
HeteroMorpheus: Universal Control Based on Morphological Heterogeneity ModelingCode0
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task GenerationCode1
ChordSync: Conformer-Based Alignment of Chord Annotations to Music Audio—0
Diff3DETR:Agent-based Diffusion Model for Semi-supervised 3D Object Detection—0
Privacy-preserving datasets by capturing feature distributions with Conditional VAEsCode0
Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology—0
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