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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 4876–4900 of 9051 papers

TitleStatusHype
RankAug: Augmented data ranking for text classification—0
Rank diversity of languages: Generic behavior in computational linguistics—0
Ranking-aware Uncertainty for Text-guided Image Retrieval—0
Ranking in Genealogy: Search Results Fusion at Ancestry—0
Ranking with social cues: Integrating online review scores and popularity information—0
Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event—0
RAP-Net: Recurrent Attention Pooling Networks for Dialogue Response Selection—0
Rare recombination events generate sequence diversity among balancer chromosomes in Drosophila melanogaster—0
RaSim: A Range-aware High-fidelity RGB-D Data Simulation Pipeline for Real-world Applications—0
RayFlow: Instance-Aware Diffusion Acceleration via Adaptive Flow Trajectories—0
R-BI: Regularized Batched Inputs enhance Incremental Decoding Framework for Low-Latency Simultaneous Speech Translation—0
RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples—0
RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation—0
REACT: Revealing Evolutionary Action Consequence Trajectories for Interpretable Reinforcement Learning—0
Reading Recognition in the Wild—0
Reading Yule in light of the history and present of macroevolution—0
Realization of MIMO Channel Model for Spatial Diversity with Capacity and SNR Multiplexing Gains—0
Real Risks of Fake Data: Synthetic Data, Diversity-Washing and Consent Circumvention—0
Real-Time Hair Rendering using Sequential Adversarial Networks—0
Real-Time Visual Analysis of High-Volume Social Media Posts—0
Real-World Depth Recovery via Structure Uncertainty Modeling and Inaccurate GT Depth Fitting—0
ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains—0
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training—0
Rebuilding Trust: Queer in AI Approach to Artificial Intelligence Risk Management—0
Recent advances and opportunities in scene classification of aerial images with deep models—0
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