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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 3751–3775 of 9051 papers

TitleStatusHype
Diverse Projection Ensembles for Distributional Reinforcement Learning—0
FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition—0
Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric Visual Data—0
Cooperative Intergroup Mating Can Overcome Ethnocentrism in Diverse Populations—0
ADLM -- stega: A Universal Adaptive Token Selection Algorithm for Improving Steganographic Text Quality via Information Entropy—0
Diverse Priors for Deep Reinforcement Learning—0
Angle Diversity Trasmitter For High Speed Data Center Uplink Communications—0
Flow-based Image-to-Image Translation with Feature Disentanglement—0
3D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models—0
Angle diversity receiver as a key enabler for reliable ORIS-based Visible Light Communication—0
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds—0
Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer—0
Flow Score Distillation for Diverse Text-to-3D Generation—0
Fluctuating growth rates link turnover and unevenness in species-rich communities—0
Generative Design through Quality-Diversity Data Synthesis and Language Models—0
FMiFood: Multi-modal Contrastive Learning for Food Image Classification—0
FM Tone Transfer with Envelope Learning—0
Focus Attention: Promoting Faithfulness and Diversity in Summarization—0
Focus-Consistent Multi-Level Aggregation for Compositional Zero-Shot Learning—0
Focusing Image Generation to Mitigate Spurious Correlations—0
Boosting Diffusion Model for Spectrogram Up-sampling in Text-to-speech: An Empirical Study—0
Offline Diversity Maximization Under Imitation Constraints—0
FONT: Flow-guided One-shot Talking Head Generation with Natural Head Motions—0
Font Identification in Historical Documents Using Active Learning—0
A COLD Approach to Generating Optimal Samples—0
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