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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

Showing 15761600 of 9051 papers

TitleStatusHype
Diverse Image-to-Image Translation via Disentangled RepresentationsCode1
Open Source Automatic Speech Recognition for GermanCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
CrowdHuman: A Benchmark for Detecting Human in a CrowdCode1
On the effectiveness of task granularity for transfer learningCode1
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesionsCode1
KonIQ-10k: Towards an ecologically valid and large-scale IQA databaseCode1
Diversity is All You Need: Learning Skills without a Reward FunctionCode1
Texygen: A Benchmarking Platform for Text Generation ModelsCode1
Building a Conversational Agent Overnight with Dialogue Self-PlayCode1
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial NetworkCode1
Remote Sensing Image Scene Classification: Benchmark and State of the ArtCode1
CityPersons: A Diverse Dataset for Pedestrian DetectionCode1
Unrolled Generative Adversarial NetworksCode1
Conditional Image Synthesis With Auxiliary Classifier GANsCode1
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence ModelsCode1
Frame- and Segment-Level Features and Candidate Pool Evaluation for Video Caption GenerationCode1
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading BooksCode1
How Many Topics? Stability Analysis for Topic ModelsCode1
Visual Place Recognition for Large-Scale UAV Applications0
Synthesizing Reality: Leveraging the Generative AI-Powered Platform Midjourney for Construction Worker Detection0
GEMMAS: Graph-based Evaluation Metrics for Multi Agent Systems0
Adversarial attacks to image classification systems using evolutionary algorithms0
Multi-population GAN Training: Analyzing Co-Evolutionary Algorithms0
Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning0
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