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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 6651–6700 of 9051 papers

TitleStatusHype
Disentangled Motif-aware Graph Learning for Phrase Grounding—0
SPARK: SPAcecraft Recognition leveraging Knowledge of Space Environment—0
Dynamic Matching Markets in Power Grid: Concepts and Solution using Deep Reinforcement Learning—0
Towards Algorithmic Transparency: A Diversity Perspective—0
On the Linear Ordering Problem and the Rankability of Data—0
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms—0
Population genetics in microchannels—0
Co-optimising Robot Morphology and Controller in a Simulated Open-Ended EnvironmentCode0
Variational Transformer Networks for Layout Generation—0
A hybrid ensemble method with negative correlation learning for regressionCode0
Domain Generalization with MixStyle—0
DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine ModelCode0
Perspective-corrected Spatial Referring Expression Generation for Human-Robot Interaction—0
Measuring Linguistic Diversity During COVID-19—0
Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation—0
Learning Online from Corrective Feedback: A Meta-Algorithm for Robotics—0
Channel Estimation for MIMO Space Time Coded OTFS under Doubly Selective Channels—0
Comment Section Personalization: Algorithmic, Interface, and Interaction Design—0
Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT—0
Universal Joy A Data Set and Results for Classifying Emotions Across Languages—0
Making Use of Latent Space in Language GANs for Generating Diverse Text without Pre-training—0
IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian LanguagesCode0
CFILT IIT Bombay@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion using Multilingual Representation fromTransformers—0
Expanding, Retrieving and Infilling: Diversifying Cross-Domain Question Generation with Flexible TemplatesCode0
MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts—0
cs_english@LT-EDI-EACL2021: Hope Speech Detection Based On Fine-tuning ALBERT Model—0
Implementing Evaluation Metrics Based on Theories of Democracy in News Comment Recommendation (Hackathon Report)—0
Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model—0
Exploring Implicit Sentiment Evoked by Fine-grained News Events—0
No NLP Task Should be an Island: Multi-disciplinarity for Diversity in News Recommender Systems—0
An Overview of Fairness in Data – Illuminating the Bias in Data Pipeline—0
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness—0
Findings of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion—0
KU_NLP@LT-EDI-EACL2021: A Multilingual Hope Speech Detection for Equality, Diversity, and Inclusion using Context Aware Embeddings—0
In&Out : Diverse Image Outpainting via GAN Inversion—0
WakaVT: A Sequential Variational Transformer for Waka Generation—0
Situation-Specific Multimodal Feature Adaptation—0
Abusive Language Recognition in RussianCode0
From characters to words: the turning point of BPE mergesCode0
Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section—0
IIIT_DWD@LT-EDI-EACL2021: Hope Speech Detection in YouTube multilingual comments—0
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite—0
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial TrainingCode0
Data Augmentation in a Hybrid Approach for Aspect-Based Sentiment AnalysisCode0
Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspection—0
Automated Backend-Aware Post-Training Quantization—0
Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification—0
Continual Speaker Adaptation for Text-to-Speech Synthesis—0
A Genetic Algorithm approach to Asymmetrical Blotto Games with Heterogeneous Valuations—0
Input-Output Balanced Framework for Long-tailed LiDAR Semantic Segmentation—0
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