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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 8926–8950 of 9051 papers

TitleStatusHype
Effects of discordance between species and gene trees on phylogenetic diversity conservation—0
A Data Quality Assessment Framework for AI-enabled Wireless Communication—0
Effects of Speaker Count, Duration, and Accent Diversity on Zero-Shot Accent Robustness in Low-Resource ASR—0
Efficacy of Machine-Generated Instructions—0
Efficient aggregation of face embeddings for decentralized face recognition deployments (extended version)—0
Combating Misinformation in the Arab World: Challenges & Opportunities—0
CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation—0
Efficient Distributed Framework for Collaborative Multi-Agent Reinforcement Learning—0
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning—0
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets—0
Efficient Exploration using Model-Based Quality-Diversity with Gradients—0
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards—0
Color Alignment in Diffusion—0
Efficient Fairness Testing in Large Language Models: Prioritizing Metamorphic Relations for Bias Detection—0
Efficient Learning of Locomotion Skills through the Discovery of Diverse Environmental Trajectory Generator Priors—0
Efficiently Secure Broadcasting in 5G Wireless Fog-Based-Fronthaul Networks—0
Efficient Medical VIE via Reinforcement Learning—0
Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search—0
Co-localization in Real-World Images—0
Efficient nonmyopic batch active search—0
Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search—0
Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks—0
Collecting Entailment Data for Pretraining: New Protocols and Negative Results—0
Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning—0
COLLAGE: Collaborative Human-Agent Interaction Generation using Hierarchical Latent Diffusion and Language Models—0
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