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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 6101–6150 of 9051 papers

TitleStatusHype
The Diversity Metrics of Sub-models based on SVD of Jacobians for Ensembles Adversarial Robustness—0
Delving into Rectifiers in Style-Based Image Translation—0
DVCFlow: Modeling Information Flow Towards Human-like Video Captioning—0
Expert-Guided Symmetry Detection in Markov Decision Processes—0
Resilience from Diversity: Population-based approach to harden models against adversarial attacksCode0
Constraint-based Diversification of JOP Gadgets—0
Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population—0
One-Shot Generative Domain Adaptation—0
How to Build Robust FAQ Chatbot with Controllable Question Generator?—0
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach—0
DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generation—0
Retrieval-guided Counterfactual Generation for QA—0
Enhancing Robustness of Pre-trained Language Model with Lexical Simplification—0
First the worst: Finding better gender translations during beam search—0
An Empirical Study of Finding Similar Exercises—0
Linguistic Diversity Scores for NLP Data Sets—0
Generating Diverse and High-Quality Abstractive Summaries with Variational Transformers—0
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning—0
Evaluating Inclusivity, Equity, and Accessibility of NLP Technology: A Case Study for Indian Languages—0
Assessing the Coherence Modeling Capabilities of Pretrained Transformer-based Language Models—0
Measuring HLT Research Equality of European Languages—0
A Natural Diet: Towards Improving Naturalness of Machine Translation Output—0
Computational historical linguistics and language diversity in South Asia—0
The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems—0
Diversifying Neural Text Generation with Part-of-Speech Guided Softmax and Sampling—0
Text Complexity And Linguistic Features: Is The Relationship Multilingual?—0
On the Importance of Data Size in Probing Fine-tuned Models—0
How do people talk about images? A study on open-domain conversation on images.—0
Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium—0
Rethinking and Refining the Distinct Metric—0
Words of Wisdom: Representational Harms in Learning From AI Communication—0
SHCT: A Successively Hierarchical Conditional Transformer for Controllable Paraphrase Generation—0
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities—0
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation—0
Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense Inference—0
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech—0
Synthetic Unknown Class Learning for Learning Unknowns—0
Exploring Story Generation with Multi-task Objectives in Variational Autoencoders—0
Modelling the effect of within-host dynamics on the diversity of a multi-strain pathogenCode0
Diversity-Promoting Human Motion Interpolation via Conditional Variational Auto-Encoder—0
Benchmarking deep generative models for diverse antibody sequence design—0
A Spiking Neuron Synaptic Plasticity Model Optimized for Unsupervised Learning—0
Detecting Quality Problems in Data Models by Clustering Heterogeneous Data Values—0
Global and local epidemiology of Group A Streptococcus indicates that naturally-acquired immunity is enduring and strain-specific—0
Complementary Ensemble Learning—0
Universal and data-adaptive algorithms for model selection in linear contextual bandits—0
There is no Double-Descent in Random ForestsCode0
Mito-nuclear selection induces a trade-off between species ecological dominance and evolutionary lifespanCode0
Increasing Data Diversity with Iterative Sampling to Improve Performance—0
Generating Diverse Realistic Laughter for Interactive Art—0
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