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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 851–900 of 9051 papers

TitleStatusHype
Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient SpaceCode1
Improving Adversarial Transferability with Gradient RefiningCode1
Agree to Disagree: Diversity through Disagreement for Better TransferabilityCode1
Improving Contrastive Learning on Imbalanced Data via Open-World SamplingCode1
Covariance Matrix Adaptation for the Rapid Illumination of Behavior SpaceCode1
Addressing the Elephant in the Room: Robust Animal Re-Identification with Unsupervised Part-Based Feature AlignmentCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
Active Learning by Acquiring Contrastive ExamplesCode1
Improving the Fairness of Deep Generative Models without RetrainingCode1
Cross-Covariate Gait Recognition: A BenchmarkCode1
Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata EcosystemsCode1
AbGPT: De Novo Antibody Design via Generative Language ModelingCode1
Automated segmentation and morphological characterization of placental histology images based on a single labeled imageCode1
Inherent Trade-Offs between Diversity and Stability in Multi-Task BenchmarksCode1
CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context DemonstrationsCode1
ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different DatasetsCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
Cooperative Open-ended Learning Framework for Zero-shot CoordinationCode1
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningCode1
InternLM-Law: An Open Source Chinese Legal Large Language ModelCode1
A single-cell gene expression language modelCode1
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image SteganographyCode1
Interpreting single-cell and spatial omics data using deep neural network training dynamicsCode1
DALNet: A Rail Detection Network Based on Dynamic Anchor LineCode1
Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language ModelsCode1
Controllable Text Generation via Probability Density Estimation in the Latent SpaceCode1
IR-BERT: Leveraging BERT for Semantic Search in Background Linking for News ArticlesCode1
Active learning for medical image segmentation with stochastic batchesCode1
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
Controllable Video Captioning with an Exemplar SentenceCode1
Jakiro: Boosting Speculative Decoding with Decoupled Multi-Head via MoECode1
Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image AnalysisCode1
Keiki: Towards Realistic Danmaku Generation via Sequential GANsCode1
KERPLE: Kernelized Relative Positional Embedding for Length ExtrapolationCode1
Key-Exchange Convolutional Auto-Encoder for Data Augmentation in Early Knee Osteoarthritis DetectionCode1
Controllable Group Choreography using Contrastive DiffusionCode1
Knowledge Extraction and Distillation from Large-Scale Image-Text Colonoscopy Records Leveraging Large Language and Vision ModelsCode1
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language ModelsCode1
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentCode1
Controllable and Guided Face Synthesis for Unconstrained Face RecognitionCode1
Controllable Multi-Interest Framework for RecommendationCode1
Controlling Behavioral Diversity in Multi-Agent Reinforcement LearningCode1
Contrastive Quantization with Code Memory for Unsupervised Image RetrievalCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Contrastive Syn-to-Real GeneralizationCode1
Contrastive Identity-Aware Learning for Multi-Agent Value DecompositionCode1
Large Scale Image Completion via Co-Modulated Generative Adversarial NetworksCode1
Large-scale Unsupervised Semantic SegmentationCode1
Adding Seemingly Uninformative Labels Helps in Low Data RegimesCode1
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