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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 7201–7225 of 9051 papers

TitleStatusHype
Multi-Cycle Assignment Problems with Rotational Diversity—0
Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Model—0
RPG-Palm: Realistic Pseudo-data Generation for Palmprint Recognition—0
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition—0
Analysis of Quality Diversity Algorithms for the Knapsack Problem—0
Analysis of Knowledge Tracing performance on synthesised student data—0
Rubrik's Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset—0
Ruby Teaming: Improving Quality Diversity Search with Memory for Automated Red Teaming—0
Using Geometry to Rank Evenness Measures: Towards a Deeper Understanding of Divergence—0
Analysis of genetic diversity among some Iraqi durum wheat cultivars revealed by different molecular markers—0
Analysis of function approximation and stability of general DNNs in directed acyclic graphs using un-rectifying analysis—0
Toward best research practices in AI Psychology—0
Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem—0
Runtime Analysis of Probabilistic Crowding and Restricted Tournament Selection for Bimodal Optimisation—0
Runtime Analysis of Quality Diversity Algorithms—0
RURANET++: An Unsupervised Learning Method for Diabetic Macular Edema Based on SCSE Attention Mechanisms and Dynamic Multi-Projection Head Clustering—0
Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations—0
Using Known Words to Learn More Words: A Distributional Analysis of Child Vocabulary Development—0
Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem—0
Using Large Language Models to Generate Authentic Multi-agent Knowledge Work Datasets—0
Analysis of Evolutionary Diversity Optimisation for Permutation Problems—0
S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving—0
S^3-TTA: Scale-Style Selection for Test-Time Augmentation in Biomedical Image Segmentation—0
SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation—0
SaFARi: State-Space Models for Frame-Agnostic Representation—0
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