Papers Multi-Label Classification
“Multi-Label Classification” 태그가 달린 논문 1,337편 · 필터 해제
Superclass Adversarial Attack
Adversarial attacks have only focused on changing the predictions of the classifier, but their danger greatly depends on how the class is mistaken. For example, when an automatic driving system mistakes a Persian cat for…
Adversarial AttackMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONIdentifying magnetic antiskyrmions while they form with convolutional neural networks
Chiral magnets have attracted a large amount of research interest in recent years because they support a variety of topological defects, such as skyrmions and bimerons, and allow for their observation and manipulation th…
FormMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONDecision Making for Hierarchical Multi-label Classification with Multidimensional Local Precision Rate
Hierarchical multi-label classification (HMC) has drawn increasing attention in the past few decades. It is applicable when hierarchical relationships among classes are available and need to be incorporated along with th…
ClassificationDecision MakingHierarchical Multi-label ClassificationMulti-Label Classification+1Object-Aware Self-supervised Multi-Label Learning
Multi-label Learning on Image data has been widely exploited with deep learning models. However, supervised training on deep CNN models often cannot discover sufficient discriminative features for classification. As a re…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti-Label LearningObjectOpen Vocabulary Extreme Classification Using Generative Models
The extreme multi-label classification (XMC) task aims at tagging content with a subset of labels from an extremely large label set. The label vocabulary is typically defined in advance by domain experts and assumed to c…
ClassificationExtreme Multi-Label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+3Multi-Label Logo Recognition and Retrieval based on Weighted Fusion of Neural Features
Classifying logo images is a challenging task as they contain elements such as text or shapes that can represent anything from known objects to abstract shapes. While the current state of the art for logo classification …
ClassificationImage ClassificationImage RetrievalLogo Recognition+2Jam or Cream First? Modeling Ambiguity in Neural Machine Translation with SCONES
The softmax layer in neural machine translation is designed to model the distribution over mutually exclusive tokens. Machine translation, however, is intrinsically uncertain: the same source sentence can have multiple s…
Machine TranslationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONNMT+2None Class Ranking Loss for Document-Level Relation Extraction
Document-level relation extraction (RE) aims at extracting relations among entities expressed across multiple sentences, which can be viewed as a multi-label classification problem. In a typical document, most entity pai…
Document-level Relation ExtractionEmotion ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+3Leveraging Seq2seq Language Generation for Multi-level Product Issue Identification
In a leading e-commerce business, we receive hundreds of millions of customer feedback from different text communication channels such as product reviews. The feedback can contain rich information regarding customers’ di…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONText GenerationTransfer LearningExtreme Multi-Label Classification with Label Masking for Product Attribute Value Extraction
Although most studies have treated attribute value extraction (AVE) as named entity recognition, these approaches are not practical in real-world e-commerce platforms because they perform poorly, and require canonicaliza…
AttributeAttribute Value ExtractionExtreme Multi-Label ClassificationMulti-Label Classification+4KaFSP: Knowledge-Aware Fuzzy Semantic Parsing for Conversational Question Answering over a Large-Scale Knowledge Base
In this paper, we study two issues of semantic parsing approaches to conversational question answering over a large-scale knowledge base: (1) The actions defined in grammar are not sufficient to handle uncertain reasonin…
Conversational Question AnsweringEntity DisambiguationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+2Evaluating Extreme Hierarchical Multi-label Classification
Several natural language processing (NLP) tasks are defined as a classification problem in its most complex form: Multi-label Hierarchical Extreme classification, in which items may be associated with multiple classes fr…
ClassificationHierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONHPT: Hierarchy-aware Prompt Tuning for Hierarchical Text Classification
Hierarchical text classification (HTC) is a challenging subtask of multi-label classification due to its complex label hierarchy. Recently, the pretrained language models (PLM)have been widely adopted in HTC through a fi…
ClassificationLanguage ModelingLanguage ModellingMulti-Label Classification+3CAVES: A Dataset to facilitate Explainable Classification and Summarization of Concerns towards COVID Vaccines
Convincing people to get vaccinated against COVID-19 is a key societal challenge in the present times. As a first step towards this goal, many prior works have relied on social media analysis to understand the specific c…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations
The COVID-19 pandemic has been severely impacting global society since December 2019. Massive research has been undertaken to understand the characteristics of the virus and design vaccines and drugs. The related finding…
ArticlesBenchmarkingMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONProTranslator: zero-shot protein function prediction using textual description
Accurately finding proteins and genes that have a certain function is the prerequisite for a broad range of biomedical applications. Despite the encouraging progress of existing computational approaches in protein functi…
Machine TranslationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONPrediction+1LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curation
The rapid growth of biomedical literature poses a significant challenge for curation and interpretation. This has become more evident during the COVID-19 pandemic. LitCovid, a literature database of COVID-19 related pape…
ArticlesMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONRevisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity
Due to the high human cost of annotation, it is non-trivial to curate a large-scale medical dataset that is fully labeled for all classes of interest. Instead, it would be convenient to collect multiple small partially l…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONOpen-Ended Question AnsweringPartially Labeled DatasetsDiverse Imagenet Models Transfer Better
A commonly accepted hypothesis is that models with higher accuracy on Imagenet perform better on other downstream tasks, leading to much research dedicated to optimizing Imagenet accuracy. Recently this hypothesis has be…
DiversityMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONAn Ensemble Learning Based Approach to Multi-label Power Text Classification for Fault-type Recognition
With the rapid development of ICT Custom Services (ICT CS) in power industries, the deployed power ICT CS systems mainly rely on the experience of customer service staff for fault type recognition, questioning, and answe…
ClassificationEnsemble LearningMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+5