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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 7701–7725 of 9051 papers

TitleStatusHype
Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting DiversityCode0
Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityCode0
Improving Neural Conversational Models with Entropy-Based Data FilteringCode0
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
Towards a Unified Conversational Recommendation System: Multi-task Learning via Contextualized Knowledge DistillationCode0
Towards a Unified Framework for Adaptable Problematic Content Detection via Continual LearningCode0
Beyond a Single Mode: GAN Ensembles for Diverse Medical Data GenerationCode0
Beyond Aesthetics: Cultural Competence in Text-to-Image ModelsCode0
Language-Driven Active Learning for Diverse Open-Set 3D Object DetectionCode0
EmPO: Emotion Grounding for Empathetic Response Generation through Preference OptimizationCode0
Empirical Study of Off-Policy Policy Evaluation for Reinforcement LearningCode0
Language GANs Falling ShortCode0
Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-TuningCode0
PD-GAN: Adversarial Learning for Personalized Diversity-Promoting RecommendationCode0
Improving Language Generation with Sentence Coherence ObjectiveCode0
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain DomainsCode0
VME: A Satellite Imagery Dataset and Benchmark for Detecting Vehicles in the Middle East and BeyondCode0
PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI CoordinationCode0
When Prompting Fails to Sway: Inertia in Moral and Value Judgments of Large Language ModelsCode0
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly DetectionCode0
Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High DimensionsCode0
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data AnnotationsCode0
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial ExamplesCode0
PEFT-U: Parameter-Efficient Fine-Tuning for User PersonalizationCode0
Pencils to Pixels: A Systematic Study of Creative Drawings across Children, Adults and AICode0
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