SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2151–2175 of 9051 papers

TitleStatusHype
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics—0
MoPS: Modular Story Premise Synthesis for Open-Ended Automatic Story GenerationCode1
Contrastive Learning from Synthetic Audio Doppelgängers—0
Diverse 3D Human Pose Generation in Scenes based on Decoupled Structure—0
Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal ExamplesCode2
Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models—0
Baking Symmetry into GFlowNets—0
Creativity Has Left the Chat: The Price of Debiasing Language Models—0
Select-Mosaic: Data Augmentation Method for Dense Small Object ScenesCode0
Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language ModelsCode0
URGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement—0
Boosting Diffusion Model for Spectrogram Up-sampling in Text-to-speech: An Empirical Study—0
Language Guided Skill Discovery—0
Tree balance in phylogenetic models—0
Retrieval & Fine-Tuning for In-Context Tabular Models—0
CTSyn: A Foundational Model for Cross Tabular Data Generation—0
The ULS23 Challenge: a Baseline Model and Benchmark Dataset for 3D Universal Lesion Segmentation in Computed TomographyCode1
DiNeR: a Large Realistic Dataset for Evaluating Compositional GeneralizationCode0
HateDebias: On the Diversity and Variability of Hate Speech Debiasing—0
Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition—0
CLoG: Benchmarking Continual Learning of Image Generation ModelsCode1
CityCraft: A Real Crafter for 3D City Generation—0
Bootstrapping Referring Multi-Object TrackingCode1
Diversified Batch Selection for Training AccelerationCode1
GNNAnatomy: Rethinking Model-Level Explanations for Graph Neural Networks—0
Show:102550
← PrevPage 87 of 363Next →

No leaderboard results yet.