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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 4201–4225 of 9051 papers

TitleStatusHype
Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation—0
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance—0
A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks—0
Action Understanding with Multiple Classes of Actors—0
A Bayesian Mixture Model of Temporal Point Processes with Determinantal Point Process Prior—0
EUKulele: Taxonomic annotation of the unsung eukaryotic microbes—0
Combining keyphrase extraction and lexical diversity to characterize ideas in publication titles—0
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation—0
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation—0
Combining Kernelized Autoencoding and Centroid Prediction for Dynamic Multi-objective Optimization—0
Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?—0
Ethical AI-Powered Regression Test Selection—0
Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization—0
Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage—0
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization—0
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study—0
A generative framework for conversational laughter: Its 'language model' and laughter sound synthesis—0
Estimation of Distribution Algorithms with Matrix Transpose in Bayesian Learning—0
Estimation of Bistatic Radar Detection Performance Under Discrete Clutter Conditions Using Stochastic Geometry—0
Combinatorial diversity metrics for the analysis of policy processes—0
ESSYS* Sharing #UC: An Emotion-driven Audiovisual Installation—0
Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content—0
ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems—0
ESG In Corporate Filings: An AI Perspective—0
Combating Misinformation in the Arab World: Challenges & Opportunities—0
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