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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 1001–1025 of 9051 papers

TitleStatusHype
StrandHead: Text to Strand-Disentangled 3D Head Avatars Using Hair Geometric PriorsCode1
Error Diversity Matters: An Error-Resistant Ensemble Method for Unsupervised Dependency ParsingCode0
Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic SegmentationCode1
Theoretical Analysis of Quality Diversity Algorithms for a Classical Path Planning Problem—0
Relation-Guided Adversarial Learning for Data-free Knowledge TransferCode1
Decoding OTC Government Bond Market Liquidity: An ABM Model for Market Dynamics—0
Experimental Study on the Effect of Synchronization Accuracy for Near-Field RF Wireless Power Transfer in Multi-Antenna Systems—0
Classification Drives Geographic Bias in Street Scene Segmentation—0
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and RegressionCode0
Binary or nonbinary? An evolutionary learning approach to gender identity—0
StyleDiT: A Unified Framework for Diverse Child and Partner Faces Synthesis with Style Latent Diffusion Transformer—0
The Language of Motion: Unifying Verbal and Non-verbal Language of 3D Human Motion—0
EvalGIM: A Library for Evaluating Generative Image ModelsCode2
Benchmarking Linguistic Diversity of Large Language ModelsCode0
One world, one opinion? The superstar effect in LLM responses—0
Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning tasks—0
eCARLA-scenes: A synthetically generated dataset for event-based optical flow predictionCode0
Dialogue Language Model with Large-Scale Persona Data Engineering—0
CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability—0
First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI—0
STORM: A Spatio-Temporal Factor Model Based on Dual Vector Quantized Variational Autoencoders for Financial Trading—0
Learning Camera Movement Control from Real-World Drone Videos—0
Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction—0
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation—0
Augmenting Sequential Recommendation with Balanced Relevance and DiversityCode1
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