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 1951–1975 of 9051 papers

TitleStatusHype
A Two-stage Evolutionary Framework For Multi-objective Optimization—0
Few-Shot Image Generation by Conditional Relaxing Diffusion Inversion—0
V-VIPE: Variational View Invariant Pose Embedding—0
General and Task-Oriented Video SegmentationCode1
Improving the Transferability of Adversarial Examples by Feature Augmentation—0
Beyond Aesthetics: Cultural Competence in Text-to-Image ModelsCode0
Virtual Personas for Language Models via an Anthology of BackstoriesCode1
Spatial Focused Bitemporal Interactive Network for Remote Sensing Image Change DetectionCode0
Analysis of genetic diversity among some Iraqi durum wheat cultivars revealed by different molecular markers—0
Leveraging image captions for selective whole slide image annotationCode0
MST5 -- Multilingual Question Answering over Knowledge GraphsCode0
Ada-adapter:Fast Few-shot Style Personlization of Diffusion Model with Pre-trained Image Encoder—0
Invariance Principle Meets Vicinal Risk Minimization—0
A Factuality and Diversity Reconciled Decoding Method for Knowledge-Grounded Dialogue Generation—0
3D Vision and Language Pretraining with Large-Scale Synthetic DataCode1
Sub-SA: Strengthen In-context Learning via Submodular Selective AnnotationCode0
UltraEdit: Instruction-based Fine-Grained Image Editing at ScaleCode0
Training Task Experts through Retrieval Based Distillation—0
Multi-scale Conditional Generative Modeling for Microscopic Image Restoration—0
Harmony in Diversity: Merging Neural Networks with Canonical Correlation AnalysisCode0
Progress or Regress? Self-Improvement Reversal in Post-training—0
The Solution for Language-Enhanced Image New Category Discovery—0
VRSD: Rethinking Similarity and Diversity for Retrieval in Large Language Models—0
Enhancing learning in spiking neural networks through neuronal heterogeneity and neuromodulatory signaling—0
Few-Shot Airway-Tree Modeling using Data-Driven Sparse Priors—0
Show:102550
← PrevPage 79 of 363Next →

No leaderboard results yet.