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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 3426–3450 of 9051 papers

TitleStatusHype
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect—0
Contrastive Learning from Synthetic Audio Doppelgängers—0
Contrastive Learning for Diverse Disentangled Foreground Generation—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
Active Learning with Tabular Language Models—0
Absolute Ranking: An Essential Normalization for Benchmarking Optimization Algorithms—0
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification—0
A Survey on Self-Evolution of Large Language Models—0
Contrastive Examples for Addressing the Tyranny of the Majority—0
A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality—0
AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems—0
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization—0
Continuous Inference in Graphical Models with Polynomial Energies—0
A Survey on Backbones for Deep Video Action Recognition—0
Continual Speaker Adaptation for Text-to-Speech Synthesis—0
A Survey on 3D Skeleton Based Person Re-Identification: Approaches, Designs, Challenges, and Future Directions—0
AI Fairness for People with Disabilities: Point of View—0
Active Learning Principles for In-Context Learning with Large Language Models—0
Continual Semantic Segmentation with Automatic Memory Sample Selection—0
Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images—0
A survey of part-of-speech tagging approaches applied to K’iche’—0
Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction—0
A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI—0
Contextual Distillation Model for Diversified Recommendation—0
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