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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 551–575 of 9051 papers

TitleStatusHype
Multi-head Attention-based Deep Multiple Instance LearningCode1
Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin TonesCode1
Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language ModelsCode1
WcDT: World-centric Diffusion Transformer for Traffic Scene GenerationCode1
DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language ModelCode1
A hybrid transformer and attention based recurrent neural network for robust and interpretable sentiment analysis of tweetsCode1
Enhance Image Classification via Inter-Class Image Mixup with Diffusion ModelCode1
BlendX: Complex Multi-Intent Detection with Blended PatternsCode1
HandBooster: Boosting 3D Hand-Mesh Reconstruction by Conditional Synthesis and Sampling of Hand-Object InteractionsCode1
Can 3D Vision-Language Models Truly Understand Natural Language?Code1
On Pretraining Data Diversity for Self-Supervised LearningCode1
Diversity-aware Channel Pruning for StyleGAN CompressionCode1
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial TrajectoryCode1
DreamDA: Generative Data Augmentation with Diffusion ModelsCode1
Controllable Face Synthesis with Semantic Latent Diffusion ModelsCode1
GenView: Enhancing View Quality with Pretrained Generative Model for Self-Supervised LearningCode1
Scaling Data Diversity for Fine-Tuning Language Models in Human AlignmentCode1
Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features CriticsCode1
Dyadic Interaction Modeling for Social Behavior GenerationCode1
LAFS: Landmark-based Facial Self-supervised Learning for Face RecognitionCode1
GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection MethodCode1
PromptIQA: Boosting the Performance and Generalization for No-Reference Image Quality Assessment via PromptsCode1
Unity by Diversity: Improved Representation Learning in Multimodal VAEsCode1
SIRST-5K: Exploring Massive Negatives Synthesis with Self-supervised Learning for Robust Infrared Small Target DetectionCode1
Probabilistic Topic Modelling with Transformer RepresentationsCode1
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