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

Showing 451475 of 9051 papers

TitleStatusHype
DivClust: Controlling Diversity in Deep ClusteringCode1
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial NetworkCode1
Cross-Covariate Gait Recognition: A BenchmarkCode1
Diverse and Admissible Trajectory Forecasting through Multimodal Context UnderstandingCode1
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence ModelsCode1
Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline GenerationCode1
AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic DataCode1
Diverse Generative Perturbations on Attention Space for Transferable Adversarial AttacksCode1
Diverse Image Captioning with Context-Object Split Latent SpacesCode1
Diverse Image Generation via Self-Conditioned GANsCode1
Amortizing intractable inference in large language modelsCode1
Diverse Policy Optimization for Structured Action SpaceCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
Analysis and Evaluation of Synthetic Data Generation in Speech Dysfluency DetectionCode1
Diversified Adversarial Attacks based on Conjugate Gradient MethodCode1
Diversified Batch Selection for Training AccelerationCode1
A Large-Scale Database for Graph Representation LearningCode1
A Large-Scale Study on Video Action Dataset CondensationCode1
A Large-scale Universal Evaluation Benchmark For Face Forgery DetectionCode1
Diversifying Dialog Generation via Adaptive Label SmoothingCode1
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source DataCode1
Diversity-Aware Meta Visual PromptingCode1
Diversity Enhanced Active Learning with Strictly Proper Scoring RulesCode1
Diversity-Guided MLP Reduction for Efficient Large Vision TransformersCode1
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image SteganographyCode1
Show:102550
← PrevPage 19 of 363Next →

No leaderboard results yet.