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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 2901–2925 of 9051 papers

TitleStatusHype
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness—0
Diversity Based Edge Pruning of Neural Networks Using Determinantal Point Processes—0
DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation—0
Diversity-based Design Assist for Large Legged Robots—0
Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks—0
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models—0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
Advances in Multi-turn Dialogue Comprehension: A Survey—0
DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics—0
Ensemble-based Adversarial Defense Using Diversified Distance Mapping—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
CDL: Curriculum Dual Learning for Emotion-Controllable Response Generation—0
Dropping diversity of products of large US firms: Models and measures—0
Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes—0
Diversity-aware Web APIs Recommendation with Compatibility Guarantee—0
DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling—0
DTSGAN: Learning Dynamic Textures via Spatiotemporal Generative Adversarial Network—0
BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation—0
Diversity-aware social robots meet people: beyond context-aware embodied AI—0
Diversity-Aware Sign Language Production through a Pose Encoding Variational Autoencoder—0
Dual-CNN: A Convolutional language decoder for paragraph image captioning—0
Brush2Prompt: Contextual Prompt Generator for Object Inpainting—0
Dual-Force: Enhanced Offline Diversity Maximization under Imitation Constraints—0
Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection—0
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