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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

Showing 26012625 of 9051 papers

TitleStatusHype
Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh RecoveryCode0
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization0
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea0
An Improved Dung Beetle Optimizer for Random Forest Optimization0
Multi-ToM: Evaluating Multilingual Theory of Mind Capabilities in Large Language Models0
LetsTalk: Latent Diffusion Transformer for Talking Video Synthesis0
ChemSafetyBench: Benchmarking LLM Safety on Chemistry DomainCode0
Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration0
The 1st Workshop on Human-Centered Recommender Systems0
TPLogAD: Unsupervised Log Anomaly Detection Based on Event Templates and Key Parameters0
Brain-Computer Interfaces for Emotional Regulation in Patients with Various Disorders0
Reconciling Semantic Controllability and Diversity for Remote Sensing Image Synthesis with Hybrid Semantic Embedding0
Is there a robust effect of mainland mutualism rates on species richness of oceanic islands?Code0
On the Fairness, Diversity and Reliability of Text-to-Image Generative Models0
From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption0
Out-Of-Distribution Detection with Diversification (Provably)Code0
Open Challenges in the Formal Verification of Autonomous Driving0
Which Channel in 6G, Low-rank or Full-rank, more needs RIS from a Perspective of DoF?0
Unification of Balti and trans-border sister dialects in the essence of LLMs and AI Technology0
Identity Preserving 3D Head Stylization with Multiview Score Distillation0
LIMBA: An Open-Source Framework for the Preservation and Valorization of Low-Resource Languages using Generative Models0
Utilizing Large Language Models to Synthesize Product Desirability Datasets0
Exploring Non-Linear Effects of Built Environment on Travel Using an Integrated Machine Learning and Inferential Modeling Approach: A Three-Wave Repeated Cross-Sectional Study0
CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval0
Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity0
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