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 1776–1800 of 9051 papers

TitleStatusHype
A Block-Based Adaptive Decoupling Framework for Graph Neural NetworksCode0
Concept-as-Tree: Synthetic Data is All You Need for VLM PersonalizationCode0
ComSD: Balancing Behavioral Quality and Diversity in Unsupervised Skill DiscoveryCode0
Increasing Entropy to Boost Policy Gradient Performance on Personalization TasksCode0
Computing recommendations via a Knowledge Graph-aware AutoencoderCode0
A Simple Yet Effective Approach for Diversified Session-Based RecommendationCode0
Improving Transferability of Adversarial Examples with Input DiversityCode0
Active Learning for Abstractive Text SummarizationCode0
Consistency-based anomaly detection with adaptive multiple-hypotheses predictionsCode0
Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence PairsCode0
Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal StudyCode0
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
Improving the Diversity of Unsupervised Paraphrasing with Embedding OutputsCode0
Is Depth All You Need? An Exploration of Iterative Reasoning in LLMsCode0
A Simple Method for Commonsense ReasoningCode0
Improving the Evaluation of Generative Models with Fuzzy LogicCode0
A Hierarchical Deep Learning Approach for Minority Instrument DetectionCode0
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding ExplorationCode0
A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddingsCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
A Simple, Fast Diverse Decoding Algorithm for Neural GenerationCode0
To Ensemble or Not Ensemble: When does End-To-End Training Fail?Code0
JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy LearningCode0
Computational detection of antigen specific B cell receptors following immunizationCode0
Improving Screening Processes via Calibrated Subset SelectionCode0
Show:102550
← PrevPage 72 of 363Next →

No leaderboard results yet.