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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 7976–8000 of 9051 papers

TitleStatusHype
Text-based LSTM networks for Automatic Music CompositionCode0
Leveraging Open Knowledge for Advancing Task Expertise in Large Language ModelsCode0
Sentiment-oriented Transformer-based Variational Autoencoder Network for Live Video CommentingCode0
Towards Effective Data-Free Knowledge Distillation via Diverse Diffusion AugmentationCode0
Separating Content and Style for Unsupervised Image-to-Image TranslationCode0
Controlling Diversity at Inference: Guiding Diffusion Recommender Models with Targeted Category PreferencesCode0
Controlled Evaluation of Syntactic Knowledge in Multilingual Language ModelsCode0
Sequence-to-Sequence Data Augmentation for Dialogue Language UnderstandingCode0
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity SamplingCode0
Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh RecoveryCode0
DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse TasksCode0
PoseAugment: Generative Human Pose Data Augmentation with Physical Plausibility for IMU-based Motion CaptureCode0
AGAIN: Adversarial Training With Attribution Span Enlargement and Hybrid Feature FusionCode0
How Does A Text Preprocessing Pipeline Affect Ontology Syntactic Matching?Code0
Towards Efficiently Diversifying Dialogue Generation via Embedding AugmentationCode0
A Corpus for Reasoning About Natural Language Grounded in PhotographsCode0
Pose-Selective Max Pooling for Measuring SimilarityCode0
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversionCode0
Lightning-fast adaptive immune receptor similarity search by symmetric deletion lookupCode0
Lightweight Adaptation of Neural Language Models via Subspace EmbeddingCode0
Dreaddit: A Reddit Dataset for Stress Analysis in Social MediaCode0
HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of DocumentsCode0
Asymptotic theory of in-context learning by linear attentionCode0
Higher-Order Message Passing for Glycan Representation LearningCode0
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