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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 8951–8975 of 9051 papers

TitleStatusHype
Efficient Sampling for k-Determinantal Point Processes—0
Efficient Scene Recovery Using Luminous Flux Prior—0
Efficient Self-Supervised Data Collection for Offline Robot Learning—0
Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity—0
An Efficient Framework for Crediting Data Contributors of Diffusion Models—0
Efficient Skill Discovery via Regret-Aware Optimization—0
Test-Optional Admissions—0
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks—0
Efficient Transfer Learning in Diffusion Models via Adversarial Noise—0
Test-time Adaptation for Cross-modal Retrieval with Query Shift—0
Collaborative Training of GANs in Continuous and Discrete Spaces for Text Generation—0
Ego2HandsPose: A Dataset for Egocentric Two-hand 3D Global Pose Estimation—0
Ego-Downward and Ambient Video based Person Location Association—0
Collaborative Perception Datasets in Autonomous Driving: A Survey—0
Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems—0
Collaborative Machine Learning Model Building with Families Using Co-ML—0
e-Health CSIRO at RRG24: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation—0
Elicitron: An LLM Agent-Based Simulation Framework for Design Requirements Elicitation—0
Eligibility traces provide a data-inspired alternative to backpropagation through time—0
ELITE: Enhanced Language-Image Toxicity Evaluation for Safety—0
ELSA: A Style Aligned Dataset for Emotionally Intelligent Language Generation—0
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models—0
Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems—0
Collaborative Data Relabeling for Robust and Diverse Voice Apps Recommendation in Intelligent Personal Assistants—0
Co-Learning Empirical Games and World Models—0
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