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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 5201–5225 of 9051 papers

TitleStatusHype
Improving Personalized Explanation Generation through Visualization—0
KSAM: Infusing Multi-Source Knowledge into Dialogue Generation via Knowledge Source Aware Multi-Head Decoding—0
Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia—0
NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM—0
Corpus Development of Kiswahili Speech Recognition Test and Evaluation sets, Preemptively Mitigating Demographic Bias Through Collaboration with Linguists—0
Overview of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion—0
giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI—0
IIT Dhanbad @LT-EDI-ACL2022- Hope Speech Detection for Equality, Diversity, and Inclusion—0
Bridging the Gap between Recognition-level Pre-training and Commonsensical Vision-language Tasks—0
IIITSurat@LT-EDI-ACL2022: Hope Speech Detection using Machine Learning—0
IDIAP_TIET@LT-EDI-ACL2022 : Hope Speech Detection in Social Media using Contextualized BERT with Attention MechanismCode0
IDIAP Submission@LT-EDI-ACL2022 : Hope Speech Detection for Equality, Diversity and InclusionCode0
IDIAP Submission@LT-EDI-ACL2022: Homophobia/Transphobia Detection in social media commentsCode0
CURAJ_IIITDWD@LT-EDI-ACL 2022: Hope Speech Detection in English YouTube Comments using Deep Learning Techniques—0
Predicting scalar diversity with context-driven uncertainty over alternatives—0
Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense InferenceCode1
SSNCSE_NLP@LT-EDI-ACL2022:Hope Speech Detection for Equality, Diversity and Inclusion using sentence transformers—0
SSN_ARMM@ LT-EDI -ACL2022: Hope Speech Detection for Equality, Diversity, and Inclusion Using ALBERT model—0
Towards Human Evaluation of Mutual Understanding in Human-Computer Spontaneous Conversation: An Empirical Study of Word Sense Disambiguation for Naturalistic Social Dialogs in American English—0
MUCIC@LT-EDI-ACL2022: Hope Speech Detection using Data Re-Sampling and 1D Conv-LSTM—0
LPS@LT-EDI-ACL2022:An Ensemble Approach about Hope Speech Detection—0
SOA_NLP@LT-EDI-ACL2022: An Ensemble Model for Hope Speech Detection from YouTube Comments—0
A Randomized Link Transformer for Diverse Open-Domain Dialogue Generation—0
Practice Makes a Solver Perfect: Data Augmentation for Math Word Problem SolversCode0
Towards Feature Distribution Alignment and Diversity Enhancement for Data-Free Quantization—0
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