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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 6601–6625 of 9051 papers

TitleStatusHype
LiveChat: Video Comment Generation from Audio-Visual Multimodal Contexts—0
LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering—0
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces—0
LLM-Driven E-Commerce Marketing Content Optimization: Balancing Creativity and Conversion—0
LLM4Rerank: LLM-based Auto-Reranking Framework for Recommendations—0
LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detection—0
LLMs grasp morality in concept—0
LLMs Prompted for Graphs: Hallucinations and Generative Capabilities—0
LLMs Lost in Translation: M-ALERT uncovers Cross-Linguistic Safety Gaps—0
LLM-TAKE: Theme Aware Keyword Extraction Using Large Language Models—0
LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation—0
LMGQS: A Large-scale Dataset for Query-focused Summarization—0
Local adaptation, phenotypic plasticity, and species coexistence—0
Local and collective transitions in sparsely-interacting ecological communities—0
Local Attention Pyramid for Scene Image Generation—0
Local Diversity and Ultra-Reliable Antenna Arrays—0
Local Implicit Grid Representations for 3D Scenes—0
Internal Feedback in Biological Control: Diversity, Delays, and Standard Theory—0
Localization and Expansion: A Decoupled Framework for Point Cloud Few-shot Semantic Segmentation—0
Localized Lasso for High-Dimensional Regression—0
Locally Weighted Ensemble Clustering—0
Local Magnification for Data and Feature Augmentation—0
Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential—0
Local Relationship Learning With Person-Specific Shape Regularization for Facial Action Unit Detection—0
Location-based Initial Access for Wireless Power Transfer with Physically Large Arrays—0
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