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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 5701–5750 of 9051 papers

TitleStatusHype
FABRA: French Aggregator-Based Readability Assessment toolkit—0
The ALPIN Sentiment Dictionary: Austrian Language Polarity in Newspapers—0
MAKED: Multi-lingual Automatic Keyword Extraction Dataset—0
Design and Evaluation of the Corpus of Everyday Japanese Conversation—0
Construction of Responsive Utterance Corpus for Attentive Listening Response Production—0
The LTRC Hindi-Telugu Parallel Corpus—0
MAD-EN: Microarchitectural Attack Detection through System-wide Energy ConsumptionCode0
Critic Sequential Monte Carlo—0
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image CaptioningCode0
CIGMO: Categorical invariant representations in a deep generative frameworkCode0
DiMA: Sequence Diversity Dynamics Analyser for Viruses—0
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning—0
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality—0
Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis—0
DFM: Dialogue Foundation Model for Universal Large-Scale Dialogue-Oriented Task Learning—0
Evaluating the Diversity, Equity and Inclusion of NLP Technology: A Case Study for Indian Languages—0
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization—0
Pneumococcus and the stress-gradient hypothesis: a trade-off links R_0 and susceptibility to co-colonization across countries—0
Principled Paraphrase Generation with Parallel CorporaCode0
Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model—0
Symptom Identification for Interpretable Detection of Multiple Mental Disorders—0
User Clustering for Rate Splitting using Machine Learning—0
Looking for a Handsome Carpenter! Debiasing GPT-3 Job AdvertisementsCode0
Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining DatasetsCode0
Diversity Enhanced Table-to-Text Generation via Type Control—0
Covariance Matrix Adaptation MAP-Annealing—0
AFEC: A Knowledge Graph Capturing Social Intelligence in Casual Conversations—0
Unsupervised Sign Language Phoneme Clustering using HamNoSys Notation—0
Diversity Preference-Aware Link Recommendation for Online Social Networks—0
Diversity vs. Recognizability: Human-like generalization in one-shot generative modelsCode0
StyLitGAN: Prompting StyleGAN to Produce New Illumination Conditions—0
Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection—0
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble—0
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?—0
Simple Regularisation for Uncertainty-Aware Knowledge Distillation—0
Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational BayesCode0
GPoeT-2: A GPT-2 Based Poem GeneratorCode0
RandoMix: A mixed sample data augmentation method with multiple mixed modes—0
Pluralistic Image Completion with Probabilistic Mixture-of-Experts—0
Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification—0
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
Accented Speech Recognition: Benchmarking, Pre-training, and Diverse Data—0
Many Field Packet Classification with Decomposition and Reinforcement Learning—0
The Diversity of Argument-Making in the Wild: from Assumptions and Definitions to Causation and Anecdote in Reddit's "Change My View"—0
Practical Insights of Repairing Model Problems on Image Classification—0
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement LearningCode0
StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map—0
Efficient and Training-Free Control of Language Generation—0
kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval—0
Beyond Static Models and Test Sets: Benchmarking the Potential of Pre-trained Models Across Tasks and Languages—0
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