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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 5801–5850 of 9051 papers

TitleStatusHype
Overview of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion—0
Predicting scalar diversity with context-driven uncertainty over alternatives—0
Bridging the Gap between Recognition-level Pre-training and Commonsensical Vision-language Tasks—0
Towards Feature Distribution Alignment and Diversity Enhancement for Data-Free Quantization—0
Practice Makes a Solver Perfect: Data Augmentation for Math Word Problem SolversCode0
Local adaptation, phenotypic plasticity, and species coexistence—0
Mind the gap: how multiracial individuals get left behind when we talk about race, ethnicity, and ancestry in genomic research—0
A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning ModelsCode0
On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference—0
Towards assessing agricultural land suitability with causal machine learning—0
Probing Simile Knowledge from Pre-trained Language ModelsCode0
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning—0
CapOnImage: Context-driven Dense-Captioning on Image—0
A Robust Contrastive Alignment Method For Multi-Domain Text Classification—0
Bias-Variance Decompositions for Margin Losses—0
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition—0
Loss-based Sequential Learning for Active Domain Adaptation—0
STC-IDS: Spatial-Temporal Correlation Feature Analyzing based Intrusion Detection System for Intelligent Connected Vehicles—0
Selective clustering ensemble based on kappa and F-score—0
Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition—0
A Vocabulary-Free Multilingual Neural Tokenizer for End-to-End Task Learning—0
DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation—0
Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research—0
Relevance-guided Unsupervised Discovery of Abilities with Quality-Diversity Algorithms—0
Self-paced Multi-grained Cross-modal Interaction Modeling for Referring Expression Comprehension—0
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural NetworksCode0
New confidence interval methods for Shannon index—0
Event Transition Planning for Open-ended Text GenerationCode0
FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing FlowCode0
G2GT: Retrosynthesis Prediction with Graph to Graph Attention Neural Network and Self-TrainingCode0
Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies—0
Image Data Augmentation for Deep Learning: A Survey—0
Diverse Imagenet Models Transfer Better—0
Dynamic Network Adaptation at Inference—0
Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport—0
Entropy-based Active Learning for Object Detection with Progressive Diversity Constraint—0
Improving Pre-trained Language Models with Syntactic Dependency Prediction Task for Chinese Semantic Error Recognition—0
Spatio-Temporal-Frequency Graph Attention Convolutional Network for Aircraft Recognition Based on Heterogeneous Radar Network—0
Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Model—0
A collaborative decomposition-based evolutionary algorithm integrating normal and penalty-based boundary intersection for many-objective optimization—0
Dynamic Diagnosis of the Progress and Shortcomings of Student Learning using Machine Learning based on Cognitive, Social, and Emotional Features—0
Population Diversity Leads to Short Running Times of Lexicase Selection—0
Clinical trial site matching with improved diversity using fair policy learning—0
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight SharingCode0
A Universality-Individuality Integration Model for Dialog Act Classification—0
Mitigating Bias in Facial Analysis Systems by Incorporating Label Diversity—0
Flexible Multiple-Objective Reinforcement Learning for Chip Placement—0
Benchmarking Active Learning Strategies for Materials Optimization and Discovery—0
Coevolutionary Pareto Diversity Optimization—0
Leveraging massively parallel reporter assays for evolutionary questions—0
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