Papers Multilingual text classification
“Multilingual text classification” 태그가 달린 논문 31편 · 필터 해제
The Impact of Model Scaling on Seen and Unseen Language Performance
The rapid advancement of Large Language Models (LLMs), particularly those trained on multilingual corpora, has intensified the need for a deeper understanding of their performance across a diverse range of languages and …
Machine TranslationMultilingual text classificationtext-classificationText Classification+1Comparing zero-shot self-explanations with human rationales in multilingual text classification
Instruction-tuned LLMs are able to provide an explanation about their output to users by generating self-explanations that do not require gradient computations or the application of possibly complex XAI methods. In this …
Multilingual text classificationSentiment AnalysisSentiment Classificationtext-classification+1XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples
Recent studies indicate that leveraging off-the-shelf or fine-tuned retrievers, capable of retrieving relevant in-context examples tailored to the input query, enhances few-shot in-context learning of English. However, a…
In-Context LearningLanguage ModelingLanguage ModellingLarge Language Model+5L3Cube-IndicNews: News-based Short Text and Long Document Classification Datasets in Indic Languages
In this work, we introduce L3Cube-IndicNews, a multilingual text classification corpus aimed at curating a high-quality dataset for Indian regional languages, with a specific focus on news headlines and articles. We have…
ArticlesClassificationDocument ClassificationMultilingual text classification+4Comparative Analysis of Multilingual Text Classification & Identification through Deep Learning and Embedding Visualization
This research conducts a comparative study on multilingual text classification methods, utilizing deep learning and embedding visualization. The study employs LangDetect, LangId, FastText, and Sentence Transformer on a d…
ClassificationClusteringMultilingual text classificationSentence+2Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification
Adapters and Low-Rank Adaptation (LoRA) are parameter-efficient fine-tuning techniques designed to make the training of language models more efficient. Previous results demonstrated that these methods can even improve pe…
ClassificationMultilingual text classificationparameter-efficient fine-tuningtext-classification+1Exploring Multilingual Text Data Distillation
With the rise of deep learning, large datasets and complex models have become common, requiring significant computing power. To address this, data distillation has emerged as a technique to quickly train models with lowe…
Dataset DistillationFairnessLanguage ModelingLanguage Modelling+3Model and Evaluation: Towards Fairness in Multilingual Text Classification
Recently, more and more research has focused on addressing bias in text classification models. However, existing research mainly focuses on the fairness of monolingual text classification models, and research on fairness…
ClassificationContrastive LearningFairnessLanguage Modelling+3MiLMo:Minority Multilingual Pre-trained Language Model
Pre-trained language models are trained on large-scale unsupervised data, and they can fine-turn the model only on small-scale labeled datasets, and achieve good results. Multilingual pre-trained language models can be t…
ClassificationLanguage ModelingLanguage Modellingmodel+3SLICER: Sliced Fine-Tuning for Low-Resource Cross-Lingual Transfer for Named Entity Recognition
Large multilingual language models generally demonstrate impressive results in zero-shot cross-lingual transfer, yet often fail to successfully transfer to low-resource languages, even for token-level prediction tasks li…
Cross-Lingual TransferMultilingual text classificationnamed-entity-recognitionNamed Entity Recognition+3muBoost: An Effective Method for Solving Indic Multilingual Text Classification Problem
Text Classification is an integral part of many Natural Language Processing tasks such as sarcasm detection, sentiment analysis and many more such applications. Many e-commerce websites, social-media/entertainment platfo…
Multilingual text classificationSarcasm DetectionSentiment Analysistext-classification+1Easy Adaptation to Mitigate Gender Bias in Multilingual Text Classification
Existing approaches to mitigate demographic biases evaluate on monolingual data, however, multilingual data has not been examined. In this work, we treat the gender as domains (e.g., male vs. female) and present a standa…
Domain AdaptationHate Speech DetectionMultilingual text classificationtext-classification+1Graph Neural Network Enhanced Language Models for Efficient Multilingual Text Classification
Online social media works as a source of various valuable and actionable information during disasters. These information might be available in multiple languages due to the nature of user generated content. An effective …
Graph Neural NetworkMultilingual text classificationtext-classificationText ClassificationMultilingual Text Classification for Dravidian Languages
As the fourth largest language family in the world, the Dravidian languages have become a research hotspot in natural language processing (NLP). Although the Dravidian languages contain a large number of languages, there…
ClassificationMultilingual text classificationMulti-Task Learningtext-classification+1Efficient Multilingual Text Classification for Indian Languages
India is one of the richest language hubs on the earth and is very diverse and multilingual. But apart from a few Indian languages, most of them are still considered to be resource poor. Since most of the NLP techniques …
ClassificationMultilingual text classificationtext-classificationText Classification+1ALEM at CASE 2021 Task 1: Multilingual Text Classification on News Articles
We participated CASE shared task in ACL-IJCNLP 2021. This paper is a summary of our experiments and ideas about this shared task. For each subtask we shared our approach, successful and failed methods and our thoughts ab…
ArticlesData AugmentationMultilingual text classificationtext-classification+1A Primer on Pretrained Multilingual Language Models
Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.} have emerged as a viable option for bringing the power of pretraining to a large number of languages. Given their success in zero-shot transf…
Joint Multilingual Sentence RepresentationsMultilingual text classificationMultilingual Word EmbeddingsPretrained Multilingual Language Models+3Practical Transformer-based Multilingual Text Classification
Transformer-based methods are appealing for multilingual text classification, but common research benchmarks like XNLI (Conneau et al., 2018) do not reflect the data availability and task variety of industry applications…
ClassificationData AugmentationMultilingual text classificationtext-classification+1NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers
The increasing accessibility of the internet facilitated social media usage and encouraged individuals to express their opinions liberally. Nevertheless, it also creates a place for content polluters to disseminate offen…
Multilingual text classificationXLM-RNLP-CUET@LT-EDI-EACL2021: Multilingual Code-Mixed Hope Speech Detection using Cross-lingual Representation Learner
In recent years, several systems have been developed to regulate the spread of negativity and eliminate aggressive, offensive or abusive contents from the online platforms. Nevertheless, a limited number of researches ca…
Hope Speech DetectionMultilingual text classification