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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 8851–8875 of 9051 papers

TitleStatusHype
Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization—0
Combining RGB and Points to Predict Grasping Region for Robotic Bin-Picking—0
Dynamic Island Model based on Spectral Clustering in Genetic Algorithm—0
Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?—0
Dynamic Matching Markets in Power Grid: Concepts and Solution using Deep Reinforcement Learning—0
Dynamic Multi-Objective Lion Swarm Optimization with Multi-strategy Fusion: An application in 6R robot trajectory planning—0
Dynamic Network Adaptation at Inference—0
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks—0
Dynamic Post-Hoc Neural Ensemblers—0
A Dataset of Inertial Measurement Units for Handwritten English Alphabets—0
Dynamic Range Independent Image Quality Assessment—0
Template-based eukaryotic genome editing directed by SviCas3—0
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires—0
Dynamic Scale Inference by Entropy Minimization—0
Dynamics of Algorithmic Content Amplification on TikTok—0
WakaVT: A Sequential Variational Transformer for Waka Generation—0
Dynamics of Transient Structure in In-Context Linear Regression Transformers—0
Dynamic Stochastic Decoding Strategy for Open-Domain Dialogue Generation—0
Dynamic Stochastic Ensemble with Adversarial Robust Lottery Ticket Subnetworks—0
Dynamic Swarm Dispersion in Particle Swarm Optimization for Mining Unsearched Area in Solution Space (DSDPSO)—0
Temporal Distinct Representation Learning for Action Recognition—0
Temporal Regularization Makes Your Video Generator Stronger—0
DynScene: Scalable Generation of Dynamic Robotic Manipulation Scenes for Embodied AI—0
DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognition—0
DySR: A Dynamic Representation Learning and Aligning based Model for Service Bundle Recommendation—0
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