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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 7926–7950 of 9051 papers

TitleStatusHype
HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive RegularizationCode0
Correlation and Navigation in the Vocabulary Key Representation Space of Language ModelsCode0
DuetSim: Building User Simulator with Dual Large Language Models for Task-Oriented DialoguesCode0
XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer SamplesCode0
Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural NetworkCode0
How well do you know your summarization datasets?Code0
Pointer-Guided Pre-Training: Infusing Large Language Models with Paragraph-Level Contextual AwarenessCode0
PointGrow: Autoregressively Learned Point Cloud Generation with Self-AttentionCode0
Towards Diversity-tolerant RDF-storesCode0
Dual-Teacher Ensemble Models with Double-Copy-Paste for 3D Semi-Supervised Medical Image SegmentationCode0
Dual-Representation Interaction Driven Image Quality Assessment with Restoration AssistanceCode0
Semi-supervised Chinese Poem-to-Painting Generation via Cycle-consistent Adversarial NetworksCode0
Towards Robust Neural Networks via Orthogonal DiversityCode0
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?Code0
LEATHER: A Framework for Learning to Generate Human-like Text in DialogueCode0
Leave No One Behind: Enhancing Diversity While Maintaining Accuracy in Social RecommendationCode0
Synthetic Hyperspectral Array Video Database with Applications to Cross-Spectral Reconstruction and Hyperspectral Video CodingCode0
Semi-Supervised Deep Ensembles for Blind Image Quality AssessmentCode0
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion ModelsCode0
LENAS: Learning-based Neural Architecture Search and Ensemble for 3D Radiotherapy Dose PredictionCode0
How Well Do LLMs Identify Cultural Unity in Diversity?Code0
How to partition diversityCode0
Correcting Exposure Bias for Link RecommendationCode0
LesionMix: A Lesion-Level Data Augmentation Method for Medical Image SegmentationCode0
DUAL: Diversity and Uncertainty Active Learning for Text SummarizationCode0
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