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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6751–6800 of 9051 papers

TitleStatusHype
Measuring Feature Diversity in Native Language Identification—0
Measuring GAN Training in Real Time—0
Measuring Grammatical Diversity from Small Corpora: Derivational Entropy Rates, Mean Length of Utterances, and Annotation Invariance—0
Measuring HLT Research Equality of European Languages—0
Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation—0
Measuring Lexical Diversity in Texts: The Twofold Length Problem—0
Measuring Linguistic Diversity During COVID-19—0
Smartphone Data Reveal Neighborhood-Level Racial Disparities in Police Presence—0
Measuring Sample Quality with Diffusions—0
Measuring Variety, Balance, and Disparity: An Analysis of Media Coverage of the 2021 German Federal Election—0
Mechanics promotes coherence in heterogeneous active media—0
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks—0
Medical visual question answering using joint self-supervised learning—0
MEDTalk: Multimodal Controlled 3D Facial Animation with Dynamic Emotions by Disentangled Embedding—0
MEESO: A Multi-objective End-to-End Self-Optimized Approach for Automatically Building Deep Learning Models—0
Meeting the 2020 Duolingo Challenge on a Shoestring—0
MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models—0
Melanoma Detection with Uncertainty Quantification—0
MEMD: A Diversity-Promoting Learning Framework for Short-Text Conversation—0
Meme and Variations: A Computer Model of Cultural Evolution—0
MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition—0
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory—0
Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect—0
Mental Workload and Language Production in Non-Native Speaker IPA Interaction—0
MergeUp-augmented Semi-Weakly Supervised Learning for WSI Classification—0
Mesure simultanée des réponses impulsionnelles en macrodiversité—0
Meta Adaptation using Importance Weighted Demonstrations—0
MetaCleaner: Learning to Hallucinate Clean Representations for Noisy-Labeled Visual Recognition—0
Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation—0
Meta-Diversity Search in Complex Systems, A Recipe for Artificial Open-Endedness ?—0
Meta-FL: A Novel Meta-Learning Framework for Optimizing Heterogeneous Model Aggregation in Federated Learning—0
MetaHead: An Engine to Create Realistic Digital Head—0
Metaheuristic Enhanced with Feature-Based Guidance and Diversity Management for Solving the Capacitated Vehicle Routing Problem—0
Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer—0
Meta-Learning for Few-Shot Land Cover Classification—0
Meta Learning for Multi-agent Communication—0
Two-Step Meta-Learning for Time-Series Forecasting Ensemble—0
Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning—0
MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation—0
Meta-TTT: A Meta-learning Minimax Framework For Test-Time Training—0
MetaVA: Curriculum Meta-learning and Pre-fine-tuning of Deep Neural Networks for Detecting Ventricular Arrhythmias based on ECGs—0
Metropolis-Hastings Data Augmentation for Graph Neural Networks—0
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer—0
MFR-Net: Multi-faceted Responsive Listening Head Generation via Denoising Diffusion Model—0
MGD^3: Mode-Guided Dataset Distillation using Diffusion Models—0
MGD-GAN: Text-to-Pedestrian generation through Multi-Grained Discrimination—0
MHTS: Multi-Hop Tree Structure Framework for Generating Difficulty-Controllable QA Datasets for RAG Evaluation—0
microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination—0
Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products—0
microGAN: Promoting Variety through Microbatch Discrimination—0
Show:102550
← PrevPage 136 of 182Next →

No leaderboard results yet.