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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 976–1000 of 9051 papers

TitleStatusHype
Aligning Latent and Image Spaces to Connect the UnconnectableCode1
Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolutionCode1
MultiRocket: Multiple pooling operators and transformations for fast and effective time series classificationCode1
Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain AdaptationCode1
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement LearningCode1
Adaptable Agent Populations via a Generative Model of PoliciesCode1
Multi-Task Reinforcement Learning with Mixture of Orthogonal ExpertsCode1
FastGrasp: Efficient Grasp Synthesis with DiffusionCode1
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple PredictionCode1
Biological Sequence Design with GFlowNetsCode1
DRA-GRPO: Exploring Diversity-Aware Reward Adjustment for R1-Zero-Like Training of Large Language ModelsCode1
Bilingual Mutual Information Based Adaptive Training for Neural Machine TranslationCode1
DreamDA: Generative Data Augmentation with Diffusion ModelsCode1
Augmenting Sequential Recommendation with Balanced Relevance and DiversityCode1
Neural Ensemble Search for Uncertainty Estimation and Dataset ShiftCode1
AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language ModelsCode1
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task GenerationCode1
DSDL: Data Set Description Language for Bridging Modalities and Tasks in AI DataCode1
Dual Feature Augmentation Network for Generalized Zero-shot LearningCode1
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel LossCode1
Learning a Cross-modality Anomaly Detector for Remote Sensing ImageryCode1
AdaptDiffuser: Diffusion Models as Adaptive Self-evolving PlannersCode1
FALL-E: A Foley Sound Synthesis Model and StrategiesCode1
FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMsCode1
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANsCode1
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