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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 8226–8250 of 9051 papers

TitleStatusHype
Dex1B: Learning with 1B Demonstrations for Dexterous Manipulation—0
Symmetry-Breaking Augmentations for Ad Hoc Teamwork—0
Continual Speaker Adaptation for Text-to-Speech Synthesis—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
DFlow: Diverse Dialogue Flow Simulation with Large Language Models—0
Symmetry-constrained Rectification Network for Scene Text Recognition—0
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning—0
DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning—0
Continual Semantic Segmentation with Automatic Memory Sample Selection—0
DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception—0
Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images—0
Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction—0
Contextual Distillation Model for Diversified Recommendation—0
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation—0
Context-Enhanced Detector For Building Detection From Remote Sensing Images—0
Symptom Identification for Interpretable Detection of Multiple Mental Disorders—0
DH-Set: Improving Vision-Language Alignment with Diverse and Hybrid Set-Embeddings Learning—0
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation—0
Dialect Adaptation and Data Augmentation for Low-Resource ASR: TalTech Systems for the MADASR 2023 Challenge—0
Context-Dependent Diffusion Network for Visual Relationship Detection—0
Dialect Diversity in Text Summarization on Twitter—0
Dialect-Specific Models for Automatic Speech Recognition of African American Vernacular English—0
Dialect Transfer for Swiss German Speech Translation—0
Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning—0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
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