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

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Showing 1051–1075 of 9051 papers

TitleStatusHype
EmpHi: Generating Empathetic Responses with Human-like IntentsCode1
Efficient Neural Neighborhood Search for Pickup and Delivery ProblemsCode1
Determinantal Point Process Likelihoods for Sequential RecommendationCode1
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of ExplanationsCode1
EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text ClassificationCode1
MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling ProblemCode1
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
EnvEdit: Environment Editing for Vision-and-Language NavigationCode1
Online Continual Learning on a Contaminated Data Stream with Blurry Task BoundariesCode1
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
Training-free Transformer Architecture SearchCode1
Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake DetectionCode1
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