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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

Showing 10511075 of 9051 papers

TitleStatusHype
Forcing Diffuse Distributions out of Language ModelsCode1
Fork or Fail: Cycle-Consistent Training with Many-to-One MappingsCode1
BLEU might be Guilty but References are not InnocentCode1
BlendX: Complex Multi-Intent Detection with Blended PatternsCode1
Florence-2: Advancing a Unified Representation for a Variety of Vision TasksCode1
FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live ImagesCode1
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesCode1
Fine-Grained VR Sketching: Dataset and InsightsCode1
FineRec:Exploring Fine-grained Sequential RecommendationCode1
BiRT: Bio-inspired Replay in Vision Transformers for Continual LearningCode1
BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face GenerationCode1
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical ImageryCode1
Calliar: An Online Handwritten Dataset for Arabic CalligraphyCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Biological Sequence Design with GFlowNetsCode1
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time seriesCode1
Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual FeaturesCode1
A Multimodal In-Context Tuning Approach for E-Commerce Product Description GenerationCode1
Bias Loss for Mobile Neural NetworksCode1
FFR V1.0: Fon-French Neural Machine TranslationCode1
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide GenerationCode1
Beyond Trivial Counterfactual Explanations with Diverse Valuable ExplanationsCode1
Few-Shot Video Object DetectionCode1
FHDe²Net: Full High Definition Demoireing NetworkCode1
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
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