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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 651–675 of 9051 papers

TitleStatusHype
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time seriesCode1
BlendX: Complex Multi-Intent Detection with Blended PatternsCode1
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion PredictionCode1
BLEU might be Guilty but References are not InnocentCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
Diversified Adversarial Attacks based on Conjugate Gradient MethodCode1
Boosting Human-Object Interaction Detection with Text-to-Image Diffusion ModelCode1
An Informative Tracking BenchmarkCode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
Dyadic Interaction Modeling for Social Behavior GenerationCode1
Advanced Codebook Design for SCMA-aided NTNs With Randomly Distributed UsersCode1
Dynamic Inertial Poser (DynaIP): Part-Based Motion Dynamics Learning for Enhanced Human Pose Estimation with Sparse Inertial SensorsCode1
An Empirical Study On Contrastive Search And Contrastive Decoding For Open-ended Text GenerationCode1
BoostTree and BoostForest for Ensemble LearningCode1
An Empirical Study of Vehicle Re-Identification on the AI City ChallengeCode1
Bootstrapping Referring Multi-Object TrackingCode1
Diverse Semantic Image Synthesis via Probability Distribution ModelingCode1
Diverse Policy Optimization for Structured Action SpaceCode1
Effect of latent space distribution on the segmentation of images with multiple annotationsCode1
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealingCode1
Diverse Image-to-Image Translation via Disentangled RepresentationsCode1
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process PriorsCode1
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load ForecastingCode1
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid MotionsCode1
Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary SpaceCode1
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