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 1401–1425 of 9051 papers

TitleStatusHype
Controllable Text Generation via Probability Density Estimation in the Latent SpaceCode1
LongWanjuan: Towards Systematic Measurement for Long Text QualityCode1
Data Curation Alone Can Stabilize In-context LearningCode1
LTL2Action: Generalizing LTL Instructions for Multi-Task RLCode1
Can pre-trained models assist in dataset distillation?Code1
M2m: Imbalanced Classification via Major-to-minor TranslationCode1
Controllable Video Captioning with an Exemplar SentenceCode1
Controllable Multi-Interest Framework for RecommendationCode1
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
Controlling Behavioral Diversity in Multi-Agent Reinforcement LearningCode1
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text GenerationCode1
Mask Conditional Synthetic Satellite ImageryCode1
Contrastive Syn-to-Real GeneralizationCode1
Controllable and Guided Face Synthesis for Unconstrained Face RecognitionCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Maximum Entropy Population-Based Training for Zero-Shot Human-AI CoordinationCode1
Towards Evaluating Generalist Agents: An Automated Benchmark in Open WorldCode1
CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource LanguagesCode1
ConsistencyTTA: Accelerating Diffusion-Based Text-to-Audio Generation with Consistency DistillationCode1
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation FrameworkCode1
Contrastive Quantization with Code Memory for Unsupervised Image RetrievalCode1
Controllable Group Choreography using Contrastive DiffusionCode1
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet AccuracyCode1
MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal AssistantsCode1
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-SpeechCode1
Show:102550
← PrevPage 57 of 363Next →

No leaderboard results yet.