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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 4001–4025 of 9051 papers

TitleStatusHype
FAS-assisted Wireless Powered Communication Systems—0
Grammar-based evolutionary approach for automated workflow composition with domain-specific operators and ensemble diversity—0
FedShift: Tackling Dual Heterogeneity Problem of Federated Learning via Weight Shift Aggregation—0
The effect of diversity on group decision-makingCode0
Can Shape-Infused Joint Embeddings Improve Image-Conditioned 3D Diffusion?—0
An Empirical Analysis of Diversity in Argument Summarization—0
AccentFold: A Journey through African Accents for Zero-Shot ASR Adaptation to Target Accents—0
SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling—0
Evolutionary Algorithms Simulating Molecular Evolution: A New Field Proposal—0
A fast density peak clustering based particle swarm optimizer for dynamic optimization—0
Dual-Student Knowledge Distillation Networks for Unsupervised Anomaly Detection—0
Diverse Explanations From Data-Driven and Domain-Driven Perspectives in the Physical SciencesCode0
Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias—0
Large Language Models for Mathematical Reasoning: Progresses and Challenges—0
SPECTRUM: Speaker-Enhanced Pre-Training for Long Dialogue Summarization—0
Topology-Aware Latent Diffusion for 3D Shape Generation—0
Pick-and-Draw: Training-free Semantic Guidance for Text-to-Image Personalization—0
Active Generation Network of Human Skeleton for Action Recognition—0
NNOSE: Nearest Neighbor Occupational Skill ExtractionCode0
Embracing Language Inclusivity and Diversity in CLIP through Continual Language LearningCode0
Analysis of Knowledge Tracing performance on synthesised student data—0
KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants—0
Contributing Dimension Structure of Deep Feature for Coreset SelectionCode0
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect—0
A Survey on 3D Skeleton Based Person Re-Identification: Approaches, Designs, Challenges, and Future Directions—0
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