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 5101–5125 of 9051 papers

TitleStatusHype
Towards Universal Segmentations: UniSegments 1.0—0
TeDDi Sample: Text Data Diversity Sample for Language Comparison and Multilingual NLPCode0
FABRA: French Aggregator-Based Readability Assessment toolkit—0
Makadi: A Large-Scale Human-Labeled Dataset for Hindi Semantic Parsing—0
Policy Diagnosis via Measuring Role Diversity in Cooperative Multi-agent RL—0
Exploring Diversity in Back Translation for Low-Resource Machine TranslationCode0
MAD-EN: Microarchitectural Attack Detection through System-wide Energy ConsumptionCode0
Text2Human: Text-Driven Controllable Human Image GenerationCode2
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal SystemsCode2
Critic Sequential Monte Carlo—0
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image CaptioningCode0
DiMA: Sequence Diversity Dynamics Analyser for Viruses—0
CIGMO: Categorical invariant representations in a deep generative frameworkCode0
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning—0
Revealing the Dark Secrets of Masked Image ModelingCode1
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality—0
Rethinking Fano's Inequality in Ensemble LearningCode1
DFM: Dialogue Foundation Model for Universal Large-Scale Dialogue-Oriented Task Learning—0
Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis—0
Pneumococcus and the stress-gradient hypothesis: a trade-off links R_0 and susceptibility to co-colonization across countries—0
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data AugmentationCode1
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization—0
Evaluating the Diversity, Equity and Inclusion of NLP Technology: A Case Study for Indian Languages—0
Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model—0
Principled Paraphrase Generation with Parallel CorporaCode0
Show:102550
← PrevPage 205 of 363Next →

No leaderboard results yet.