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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 3276–3300 of 9051 papers

TitleStatusHype
ERTIM@MC2: Diversified Argumentative Tweets Retrieval—0
Breaking the mold: The challenge of large scale MARL specialization—0
ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems—0
Advanced Framework for Animal Sound Classification With Features Optimization—0
ESDF: Ensemble Selection using Diversity and Frequency—0
ESG In Corporate Filings: An AI Perspective—0
ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems—0
FairSkin: Fair Diffusion for Skin Disease Image Generation—0
ESSYS* Sharing #UC: An Emotion-driven Audiovisual Installation—0
Estimation of Bistatic Radar Detection Performance Under Discrete Clutter Conditions Using Stochastic Geometry—0
Estimation of Distribution Algorithms with Matrix Transpose in Bayesian Learning—0
Diversify Question Generation with Continuous Content Selectors and Question Type Modeling—0
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization—0
Ethical AI-Powered Regression Test Selection—0
Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization—0
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation—0
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation—0
Combining keyphrase extraction and lexical diversity to characterize ideas in publication titles—0
EUKulele: Taxonomic annotation of the unsung eukaryotic microbes—0
Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation—0
Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer—0
BranchOut: Regularization for Online Ensemble Tracking With Convolutional Neural Networks—0
Combining multi-spectral data with statistical and deep-learning models for improved exoplanet detection in direct imaging at high contrast—0
An Interval-Based Bayesian Generative Model for Human Complex Activity Recognition—0
Diversifying Sparsity Using Variational Determinantal Point Processes—0
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