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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 3401–3450 of 9051 papers

TitleStatusHype
Expand and Filter: CUNI and LMU Systems for the WNGT 2020 Duolingo Shared Task—0
Expanding Chatbot Knowledge in Customer Service: Context-Aware Similar Question Generation Using Large Language Models—0
The Structure of Occupational Mobility in France—0
Diversifying Database Activity Monitoring with Bandits—0
An Instance Space Analysis of Constrained Multi-Objective Optimization Problems—0
Expansion under climate change: the genetic consequences—0
adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads—0
Fine-grained Activities of People Worldwide—0
Expedition: A Time-Aware Exploratory Search System Designed for Scholars—0
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation—0
Experimental Results of a 3D Millimeter-Wave Compressive-Reflector-Antenna Imaging System—0
Experimental Study of RCS Diversity with Novel No-divergent OAM Beams—0
Diversifying AI: Towards Creative Chess with AlphaZero—0
Experimental Validation of Coherent Joint Transmission in a Distributed-MIMO System with Analog Fronthaul for 6G—0
Both Diverse and Realism Matter: Physical Attribute and Style Alignment for Rainy Image Generation—0
Experiments on a Guarani Corpus of News and Social Media—0
Experiments on Generalizability of BERTopic on Multi-Domain Short Text—0
Expert-Agnostic Learning to Defer—0
ExpertGenQA: Open-ended QA generation in Specialized Domains—0
Expert-Guided Symmetry Detection in Markov Decision Processes—0
EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic—0
Compositional diversity in visual concept learning—0
A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems—0
Diversifying Agent's Behaviors in Interactive Decision Models—0
Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images—0
Finding Similar Medical Questions from Question Answering Websites—0
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences—0
Explicit Diversity Conditions for Effective Question Answer Generation with Large Language Models—0
Diversify and Conquer: Bandits and Diversity for an Enhanced E-commerce Homepage Experience—0
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search—0
Diversified Visual Attention Networks for Fine-Grained Object Classification—0
Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection—0
Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition—0
Exploiting Cross-Lingual Speaker and Phonetic Diversity for Unsupervised Subword Modeling—0
Diversified Texture Synthesis with Feed-forward Networks—0
Exploiting Feature Diversity for Make-up Temporal Video Grounding—0
Exploiting Joint Robustness to Adversarial Perturbations—0
Exploiting Knowledge Distillation for Few-Shot Image Generation—0
An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction—0
EXPLOITING SEMANTIC COHERENCE TO IMPROVE PREDICTION IN SATELLITE SCENE IMAGE ANALYSIS: APPLICATION TO DISEASE DENSITY ESTIMATION—0
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes—0
Exploiting Spatial-temporal Correlations for Video Anomaly Detection—0
Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning—0
Exploiting Web Images for Weakly Supervised Object Detection—0
Explorable Tone Mapping Operators—0
Exploration and Exploitation in Symbolic Regression using Quality-Diversity and Evolutionary Strategies Algorithms—0
Findings of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion—0
Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective—0
Exploratory Data Analysis of Urdu Poetry—0
Diversified Sampling Improves Scaling LLM inference—0
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