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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 4901–4925 of 9051 papers

TitleStatusHype
Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction—0
Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction—0
LAME: Layout Aware Metadata Extraction Approach for Research Articles—0
Benchmarking General-Purpose In-Context Learning—0
Benchmarking foundation models as feature extractors for weakly-supervised computational pathology—0
Landslide Geohazard Assessment With Convolutional Neural Networks Using Sentinel-2 Imagery Data—0
Land-use history impacts functional diversity across multiple trophic groups—0
Lanfrica: A Participatory Approach to Documenting Machine Translation Research on African Languages—0
LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model—0
Langsmith: An Interactive Academic Text Revision System—0
Benchmarking deep generative models for diverse antibody sequence design—0
Language-aware Interlingua for Multilingual Neural Machine Translation—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL—0
Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL—0
Language diversity and implications for Language technology in the Multilingual Europe—0
Language Diversity: Visible to Humans, Exploitable by Machines—0
Active Generation Network of Human Skeleton for Action Recognition—0
Language-driven All-in-one Adverse Weather Removal—0
Language Games as the Pathway to Artificial Superhuman Intelligence—0
Towards Diverse and Efficient Audio Captioning via Diffusion Models—0
Benchmarking Clinical Decision Support Search—0
Semantically Grounded QFormer for Efficient Vision Language Understanding—0
Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches—0
Language-Guided Self-Supervised Video Summarization Using Text Semantic Matching Considering the Diversity of the Video—0
Language Guided Skill Discovery—0
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