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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 1751–1775 of 9051 papers

TitleStatusHype
AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario—0
Data Ethics in the Era of Healthcare Artificial Intelligence in Africa: An Ubuntu Philosophy Perspective—0
A systematic dataset generation technique applied to data-driven automotive aerodynamics—0
AIR: Unifying Individual and Collective Exploration in Cooperative Multi-Agent Reinforcement Learning—0
Absolute Ranking: An Essential Normalization for Benchmarking Optimization Algorithms—0
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires—0
A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation—0
Active Task Randomization: Learning Robust Skills via Unsupervised Generation of Diverse and Feasible Tasks—0
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy—0
Data-Free Distillation of Language Model by Text-to-Text Transfer—0
Asynch-SGBDT: Asynchronous Parallel Stochastic Gradient Boosting Decision Tree based on Parameters Server—0
AIRIS2 : a Smart Gateway Diversity Algorithm for Very High-Throughput Satellite Systems—0
Active Simultaneously Transmitting and Reflecting (STAR)-RISs: Modelling and Analysis—0
Asymptotic analysis of V-BLAST MIMO for coherent optical wireless communications in Gamma-Gamma turbulence—0
Asymmetric Image Retrieval with Cross Model Compatible Ensembles—0
1000 African Voices: Advancing inclusive multi-speaker multi-accent speech synthesis—0
Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information—0
A Swiss German Dictionary: Variation in Speech and Writing—0
Active Learning with Tabular Language Models—0
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect—0
A survey on the impact of AI-based recommenders on human behaviours: methodologies, outcomes and future directions—0
AI in Support of Diversity and Inclusion—0
How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code—0
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction—0
Data-Free Neural Architecture Search via Recursive Label Calibration—0
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