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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 3451–3500 of 9051 papers

TitleStatusHype
Unbiased estimation of sampling variance for Simpson's diversity indexCode0
Can pre-trained models assist in dataset distillation?Code1
CLEVRER-Humans: Describing Physical and Causal Events the Human Way—0
Robustness-Guided Image Synthesis for Data-Free Quantization—0
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries—0
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data—0
Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning—0
scHyena: Foundation Model for Full-Length Single-Cell RNA-Seq Analysis in Brain—0
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization—0
Multimodal Question Answering for Unified Information ExtractionCode1
MUNCH: Modelling Unique 'N Controllable Heads—0
On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and BeyondCode1
Learning Diverse Skills for Local Navigation under Multi-constraint Optimality—0
Prompting Audios Using Acoustic Properties For Emotion Representation—0
Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks—0
Beyond-Accuracy: A Review on Diversity, Serendipity and Fairness in Recommender Systems Based on Graph Neural Networks—0
Exploring Model Learning Heterogeneity for Boosting Ensemble RobustnessCode0
Sieve: Multimodal Dataset Pruning Using Image Captioning ModelsCode1
Hierarchical Generation of Human-Object Interactions with Diffusion Probabilistic Models—0
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks—0
Enhancing ML-Based DoS Attack Detection Through Combinatorial Fusion Analysis—0
GenSim: Generating Robotic Simulation Tasks via Large Language ModelsCode2
Strength in Diversity: Multi-Branch Representation Learning for Vehicle Re-IdentificationCode1
No Offense Taken: Eliciting Offensiveness from Language ModelsCode0
LiveChat: Video Comment Generation from Audio-Visual Multimodal Contexts—0
An Experimental Prototype for Multistatic Asynchronous ISAC—0
A Comparative Study of Training Objectives for Clarification Facet GenerationCode0
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI ModelsCode0
Finding Pragmatic Differences Between Disciplines—0
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games—0
Sarcasm in Sight and Sound: Benchmarking and Expansion to Improve Multimodal Sarcasm Detection—0
ComSD: Balancing Behavioral Quality and Diversity in Unsupervised Skill DiscoveryCode0
Towards a Unified Framework for Adaptable Problematic Content Detection via Continual LearningCode0
Post-Training Overfitting Mitigation in DNN Classifiers—0
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling—0
Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems—0
HPL-ViT: A Unified Perception Framework for Heterogeneous Parallel LiDARs in V2V—0
SJTU-TMQA: A quality assessment database for static mesh with texture map—0
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy MaximizationCode0
Adaptive Priority Mechanisms—0
Boosting High Resolution Image Classification with Scaling-up TransformersCode0
Beauty beacon: correlated strategies for the Fisher runaway process—0
Structure Invariant Transformation for better Adversarial TransferabilityCode1
Facilitating Interdisciplinary Knowledge Transfer with Research Paper Recommender SystemsCode0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse TransformationCode1
Exploring Robot Morphology Spaces through Breadth-First Search and Random Query—0
Convolutional autoencoder-based multimodal one-class classification—0
Dual Feature Augmentation Network for Generalized Zero-shot LearningCode1
Diversify and Conquer: Bandits and Diversity for an Enhanced E-commerce Homepage Experience—0
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