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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 4651–4675 of 9051 papers

TitleStatusHype
Initial Crypto-asset Offerings (ICOs), tokenization and corporate governance—0
Innovation-exnovation dynamics on trees and trusses—0
In&Out : Diverse Image Outpainting via GAN Inversion—0
InOut: Diverse Image Outpainting via GAN Inversion—0
Bias-Variance Decompositions for Margin Losses—0
In Pursuit of Predictive Models of Human Preferences Toward AI Teammates—0
BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly—0
Active Learning with Tabular Language Models—0
Input-Output Balanced Framework for Long-tailed LiDAR Semantic Segmentation—0
Active Learning Principles for In-Context Learning with Large Language Models—0
InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions—0
In search for an alternative to the computer metaphor of the mind and brain—0
Insect Diversity Estimation in Polarimetric Lidar—0
Toward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studies—0
InsectMamba: Insect Pest Classification with State Space Model—0
Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines—0
Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias—0
Toward Model-centric Heterogeneous Federated Graph Learning: A Knowledge-driven Approach—0
Insights into Complex Brain Functions Related to Schizophrenia Disorder through Causal Network Analysis—0
Biased Random-Key Genetic Algorithms: A Review—0
Well-temperate phage: optimal bet-hedging against local environmental collapses—0
Instance-aware Remote Sensing Image Captioning with Cross-hierarchy Attention—0
Instance-based entropy fuzzy support vector machine for imbalanced data—0
Bias, diversity, and challenges to fairness in classification and automated text analysis. From libraries to AI and back—0
We Need to Measure Data Diversity in NLP -- Better and Broader—0
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