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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 3126–3150 of 9051 papers

TitleStatusHype
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation ParadigmCode1
Enhancing Molecular Property Prediction via Mixture of Collaborative ExpertsCode0
FoodFusion: A Latent Diffusion Model for Realistic Food Image Generation—0
SO-NeRF: Active View Planning for NeRF using Surrogate Objectives—0
On the Role of Edge Dependency in Graph Generative Models—0
Generating a Map of Well-being Regions using Multiscale Moving Direction Entropy on Mobile Sensors—0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction—0
A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems—0
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain ShiftsCode1
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion—0
SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World—0
WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene GenerationCode1
RetriBooru: Leakage-Free Retrieval of Conditions from Reference Images for Subject-Driven Generation—0
New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking—0
Quality Diversity in the Amorphous Fortress (QD-AF): Evolving for Complexity in 0-Player Games—0
Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images—0
Hot PATE: Private Aggregation of Distributions for Diverse Task—0
Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic SegmentationCode1
TPPoet: Transformer-Based Persian Poem Generation using Minimal Data and Advanced Decoding Techniques—0
CityGen: Infinite and Controllable 3D City Layout Generation—0
Language-driven All-in-one Adverse Weather Removal—0
Toward best research practices in AI Psychology—0
Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societies—0
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