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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 8101–8150 of 9051 papers

TitleStatusHype
Show, Control and Tell: A Framework for Generating Controllable and Grounded CaptionsCode0
Resource Mention Extraction for MOOC Discussion Forums—0
Scene Text Detection with Supervised Pyramid Context NetworkCode0
New expressions on the performance of a novel multi-hop relay-assisted hybrid FSO / RF communication system with receive diversity—0
The long-term impact of ranking algorithms in growing networks—0
A novel hybrid FSO / RF communication system with receive diversity—0
Another Diversity-Promoting Objective Function for Neural Dialogue GenerationCode0
CompoNet: Learning to Generate the Unseen by Part Synthesis and CompositionCode0
Chat More If You Like: Dynamic Cue Words Planning to Flow Longer Conversations—0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks—0
Clubmark: a Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA ArchitecturesCode0
Deep Determinantal Point Processes—0
Evolutionary Diversity Optimization Using Multi-Objective Indicators—0
Towards Large-Scale Exploratory Search over Heterogeneous Sources—0
Generating Multiple Diverse Responses for Short-Text Conversation—0
Universal and generalizable restoration strategies for degraded ecological networks—0
Modular Networks: Learning to Decompose Neural Computation—0
Parameterized Synthetic Image Data Set for Fisheye Lens—0
Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation—0
Attentive Aspect Modeling for Review-aware Recommendation—0
User Modeling for Task Oriented Dialogues—0
Diversity-Driven Extensible Hierarchical Reinforcement LearningCode0
Multi-Cycle Assignment Problems with Rotational Diversity—0
Iterative Classroom Teaching—0
Behavioural Repertoire via Generative Adversarial Policy Networks—0
Graph based Entropy for Detecting Explanatory Signs of Changes in Market—0
Student's t-Generative Adversarial Networks—0
Language GANs Falling ShortCode0
Closed-Loop Memory GAN for Continual Learning—0
The Knowref Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora ResolutionCode0
Importance of Search and Evaluation Strategies in Neural Dialogue ModelingCode0
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification—0
E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language—0
On the Generation of Medical Question-Answer Pairs—0
CariGAN: Caricature Generation through Weakly Paired Adversarial Learning—0
A Corpus for Reasoning About Natural Language Grounded in PhotographsCode0
Conceptual Content in Deep Convolutional Neural Networks: An analysis into multi-faceted properties of neurons—0
Crowdsourcing with Fairness, Diversity and Budget Constraints—0
Anomaly Detection With Multiple-Hypotheses PredictionsCode0
Inheritance-Based Diversity Measures for Explicit Convergence Control in Evolutionary Algorithms—0
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms—0
GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the WildCode0
A Convergence indicator for Multi-Objective Optimisation Algorithms—0
Middle-Out Decoding—0
Expedition: A Time-Aware Exploratory Search System Designed for Scholars—0
History by Diversity: Helping Historians search News Archives—0
Multi-Head Attention with Disagreement Regularization—0
A Neural Compositional Paradigm for Image CaptioningCode0
WikiHow: A Large Scale Text Summarization DatasetCode1
Evolutionary multiplayer games on graphs with edge diversity—0
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