SOTAVerified

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 10511100 of 9051 papers

TitleStatusHype
EmpHi: Generating Empathetic Responses with Human-like IntentsCode1
Determinantal Point Process Likelihoods for Sequential RecommendationCode1
Efficient Neural Neighborhood Search for Pickup and Delivery ProblemsCode1
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of ExplanationsCode1
MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling ProblemCode1
EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text ClassificationCode1
Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled DataCode1
Attributed Graph Clustering with Dual Redundancy ReductionCode1
Language-Grounded Indoor 3D Semantic Segmentation in the WildCode1
Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game LevelsCode1
Hierarchical Quality-Diversity for Online Damage RecoveryCode1
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise AffinityCode1
Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New BaselineCode1
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process PriorsCode1
Leverage Your Local and Global Representations: A New Self-Supervised Learning StrategyCode1
Rainbow Keywords: Efficient Incremental Learning for Online Spoken Keyword SpottingCode1
Online Continual Learning on a Contaminated Data Stream with Blurry Task BoundariesCode1
EnvEdit: Environment Editing for Vision-and-Language NavigationCode1
FS6D: Few-Shot 6D Pose Estimation of Novel ObjectsCode1
Physics Guided Deep Learning for Generative Design of Crystal Materials with Symmetry ConstraintsCode1
Implicit Neural Representations for Variable Length Human Motion GenerationCode1
Analyzing Generalization of Vision and Language Navigation to Unseen Outdoor AreasCode1
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence LearningCode1
Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake DetectionCode1
Training-free Transformer Architecture SearchCode1
Quality Controlled Paraphrase GenerationCode1
Learning Affordance Grounding from Exocentric ImagesCode1
MotionAug: Augmentation with Physical Correction for Human Motion PredictionCode1
Attribute Group Editing for Reliable Few-shot Image GenerationCode1
Complex Evolutional Pattern Learning for Temporal Knowledge Graph ReasoningCode1
InsetGAN for Full-Body Image GenerationCode1
Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph ExpertsCode1
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of RedundancyCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
Skating-Mixer: Long-Term Sport Audio-Visual Modeling with MLPsCode1
Towards Universal Texture Synthesis by Combining Texton Broadcasting with Noise Injection in StyleGAN-2Code1
Hierarchical Sketch Induction for Paraphrase GenerationCode1
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translationCode1
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular ValuesCode1
Biological Sequence Design with GFlowNetsCode1
Self-Supervised Vision Transformers Learn Visual Concepts in HistopathologyCode1
Submodlib: A Submodular Optimization LibraryCode1
VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and AdaptationCode1
Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement LearningCode1
Realistic Blur Synthesis for Learning Image DeblurringCode1
RoPGen: Towards Robust Code Authorship Attribution via Automatic Coding Style TransformationCode1
Agree to Disagree: Diversity through Disagreement for Better TransferabilityCode1
Exploring Inter-Channel Correlation for Diversity-preserved KnowledgeDistillationCode1
Approximating Gradients for Differentiable Quality Diversity in Reinforcement LearningCode1
Red Teaming Language Models with Language ModelsCode1
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