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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 4226–4250 of 9051 papers

TitleStatusHype
ESDF: Ensemble Selection using Diversity and Frequency—0
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity—0
CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation—0
A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming—0
A Decoupled 3D Facial Shape Model by Adversarial Training—0
ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems—0
ERVQ: Enhanced Residual Vector Quantization with Intra-and-Inter-Codebook Optimization for Neural Audio Codecs—0
ERTIM@MC2: Diversified Argumentative Tweets Retrieval—0
Error Typology and Remediation Strategies for Requirements Written in English by Non-Native Speakers—0
Error Propagation and Overhead Reduced Channel Estimation for RIS-Aided Multi-User mmWave Systems—0
Error performance analysis of different modulations over TWDP fading channel—0
Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks—0
Color Alignment in Diffusion—0
Co-localization in Real-World Images—0
ERNIE-Music: Text-to-Waveform Music Generation with Diffusion Models—0
ErGAN: Generative Adversarial Networks for Entity Resolution—0
Erase, then Redraw: A Novel Data Augmentation Approach for Free Space Detection Using Diffusion Model—0
FairCoT: Enhancing Fairness in Diffusion Models via Chain of Thought Reasoning of Multimodal Language Models—0
Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search—0
A Review on Quantile Regression for Stochastic Computer Experiments—0
EqGAN: Feature Equalization Fusion for Few-shot Image Generation—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
A Review on Automated Brain Tumor Detection and Segmentation from MRI of Brain—0
A General Purpose Neural Architecture for Geospatial Systems—0
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