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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

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Showing 6201–6250 of 9051 papers

TitleStatusHype
Using the Overlapping Score to Improve Corruption Benchmarks—0
Bilingual Mutual Information Based Adaptive Training for Neural Machine TranslationCode1
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding TasksCode2
A unified framework based on graph consensus term for multi-view learning—0
Focus Attention: Promoting Faithfulness and Diversity in Summarization—0
Using Geometry to Rank Evenness Measures: Towards a Deeper Understanding of Divergence—0
Towards Standard Criteria for human evaluation of Chatbots: A Survey—0
One2Set: Generating Diverse Keyphrases as a SetCode1
A review of approaches to modeling applied vehicle routing problems—0
Probabilistic Fixed Ballot Rules and Hybrid Domains—0
Orthogonal Ensemble Networks for Biomedical Image SegmentationCode0
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model SmoothnessCode0
Improving Contrastive Learning on Imbalanced Data via Open-World SamplingCode1
Profiling Pareto Front With Multi-Objective Stein Variational Gradient DescentCode1
Parallelizing Contextual Bandits—0
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index—0
On the use of feature-maps and parameter control for improved quality-diversity meta-evolution—0
High Throughput Soybean Pod-Counting with In-Field Robotic Data Collection and Machine-Vision Based Data Analysis—0
Compositional Fine-Grained Low-Shot Learning—0
Training Mixed-Objective Pointing Decoders for Block-Level Optimization in Search Recommendation—0
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks—0
A Load Balanced Recommendation Approach—0
Content-adaptive Representation Learning for Fast Image Super-resolution—0
Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection—0
An Empirical Study of Vehicle Re-Identification on the AI City ChallengeCode1
Stratified Data Integration—0
Diversity in Kemeny Rank Aggregation: A Parameterized Approach—0
Imagine, Reason and Write: Visual Storytelling with Graph Knowledge and Relational Reasoning—0
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Path-based Deep Network for Candidate Item Matching in Recommenders—0
Style-Restricted GAN: Multi-Modal Translation with Style Restriction Using Generative Adversarial NetworksCode0
Studying the association of online brand importance with museum visitors: An application of the semantic brand score—0
Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods—0
A Primer on Techtile: An R&D Testbed for Distributed Communication, Sensing and Positioning—0
Maximizing Mutual Information Across Feature and Topology Views for Learning Graph RepresentationsCode0
Plot and Rework: Modeling Storylines for Visual StorytellingCode1
On Measuring the Diversity of Organizational NetworksCode0
Do City Borders Constrain Ethnic Diversity?—0
MapGo: Model-Assisted Policy Optimization for Goal-Oriented TasksCode0
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization—0
Semantic Diversity Learning for Zero-Shot Multi-label ClassificationCode1
Learning to Generate Novel Scene Compositions from Single Images and VideosCode1
The Semantic Brand Score—0
Diffusion Models Beat GANs on Image SynthesisCode2
Towards transparency in NLP shared tasks—0
Improving Adversarial Transferability with Gradient RefiningCode1
Instance-aware Remote Sensing Image Captioning with Cross-hierarchy Attention—0
ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research—0
Efficient Self-Supervised Data Collection for Offline Robot Learning—0
Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity—0
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