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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 1076–1100 of 9051 papers

TitleStatusHype
Generative Flow Network for Listwise RecommendationCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
A Multimodal In-Context Tuning Approach for E-Commerce Product Description GenerationCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face GenerationCode1
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time seriesCode1
BlendX: Complex Multi-Intent Detection with Blended PatternsCode1
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide GenerationCode1
BiRT: Bio-inspired Replay in Vision Transformers for Continual LearningCode1
Florence-2: Advancing a Unified Representation for a Variety of Vision TasksCode1
Bacteriophage classification for assembled contigs using Graph Convolutional NetworkCode1
Fine-Grained VR Sketching: Dataset and InsightsCode1
CamContextI2V: Context-aware Controllable Video GenerationCode1
Forecasting Future World Events with Neural NetworksCode1
Fork or Fail: Cycle-Consistent Training with Many-to-One MappingsCode1
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
FineRec:Exploring Fine-grained Sequential RecommendationCode1
Bilingual Mutual Information Based Adaptive Training for Neural Machine TranslationCode1
Fractal Autoencoders for Feature SelectionCode1
Adaptively Sparse TransformersCode1
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable DiffusionCode1
Frequency Domain Model Augmentation for Adversarial AttackCode1
Bootstrapping Referring Multi-Object TrackingCode1
Biological Sequence Design with GFlowNetsCode1
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical ImageryCode1
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