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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 2651–2675 of 9051 papers

TitleStatusHype
Flickr-PAD: New Face High-Resolution Presentation Attack Detection DatabaseCode0
Diversifying Task-oriented Dialogue Response Generation with Prototype Guided ParaphrasingCode0
Behind Recommender Systems: the Geography of the ACM RecSys CommunityCode0
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and FlatnessCode0
From structure mining to unsupervised exploration of atomic octahedral networksCode0
Generating Diverse and Meaningful CaptionsCode0
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
DESTEIN: Navigating Detoxification of Language Models via Universal Steering Pairs and Head-wise Activation FusionCode0
Fine-Grained Spatiotemporal Motion Alignment for Contrastive Video Representation LearningCode0
Fine-Grained Detoxification via Instance-Level Prefixes for Large Language ModelsCode0
Topology-Preserved Human Reconstruction with DetailsCode0
Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text GenerationCode0
Finding A Voice: Evaluating African American Dialect Generation for Chatbot TechnologyCode0
Few-Shot Specific Emitter Identification via Hybrid Data Augmentation and Deep Metric LearningCode0
Few-shot Personalization of LLMs with Mis-aligned ResponsesCode0
Few-shot Quality-Diversity OptimizationCode0
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAGCode0
Few-shot Image Generation with Diffusion ModelsCode0
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Describing like humans: on diversity in image captioningCode0
Beer Organoleptic Optimisation: Utilising Swarm Intelligence and Evolutionary Computation MethodsCode0
Few-shot Image Generation via Masked DiscriminationCode0
Finer Metagenomic Reconstruction via Biodiversity OptimizationCode0
BEE: Metric-Adapted Explanations via Baseline Exploration-ExploitationCode0
DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology DiagnosisCode0
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