Papers Topic Classification
“Topic Classification” 태그가 달린 논문 186편 · 필터 해제
CTM - A Model for Large-Scale Multi-View Tweet Topic Classification
Automatically associating social media posts with topics is an important prerequisite for effective search and recommendation on many social media platforms. However, topic classification of such posts is quite challengi…
ClassificationTopic ClassificationRealistic Zero-Shot Cross-Lingual Transfer in Legal Topic Classification
We consider zero-shot cross-lingual transfer in legal topic classification using the recent MultiEURLEX dataset. Since the original dataset contains parallel documents, which is unrealistic for zero-shot cross-lingual tr…
Cross-Lingual TransferTopic ClassificationTranslationZero-Shot Cross-Lingual TransferNear-Term Advances in Quantum Natural Language Processing
This paper describes experiments showing that some tasks in natural language processing (NLP) can already be performed using quantum computers, though so far only with small datasets. We demonstrate various approaches to…
Topic ClassificationFrameASt: A Framework for Second-level Agenda Setting in Parliamentary Debates through the Lense of Comparative Agenda Topics
This paper presents a framework for studying second-level political agenda setting in parliamentary debates, based on the selection of policy topics used by political actors to discuss a specific issue on the parliamenta…
Topic ClassificationEstimating Confidence of Predictions of Individual Classifiers and TheirEnsembles for the Genre Classification Task
Genre identification is a kind of non-topic text classification. The main difference between this task and topic classification is that genre, unlike topic, usually cannot be expressed just by some keywords and is define…
Genre classificationtext-classificationText ClassificationTopic ClassificationLeveraging QA Datasets to Improve Generative Data Augmentation
The ability of generative language models (GLMs) to generate text has improved considerably in the last few years, enabling their use for generative data augmentation. In this work, we propose CONDA, an approach to furth…
Common Sense ReasoningData AugmentationQuestion AnsweringSST-2+1Improving Short Text Classification With Augmented Data Using GPT-3
GPT-3 is a large-scale natural language model developed by OpenAI that can perform many different tasks, including topic classification. Although researchers claim that it requires only a small number of in-context examp…
ClassificationLanguage ModelingLanguage Modellingtext-classification+2Sentence-level Privacy for Document Embeddings
User language data can contain highly sensitive personal content. As such, it is imperative to offer users a strong and interpretable privacy guarantee when learning from their data. In this work, we propose SentDP: pure…
Language ModelingLanguage ModellingSentenceSentiment Analysis+1CTM -- A Model for Large-Scale Multi-View Tweet Topic Classification
Automatically associating social media posts with topics is an important prerequisite for effective search and recommendation on many social media platforms. However, topic classification of such posts is quite challengi…
ClassificationTopic ClassificationClause Topic Classification in German and English Standard Form Contracts
So-called standard form contracts, i.e. contracts that are drafted unilaterally by one party, like terms and conditions of online shops or terms of services of social networks, are cornerstones of our modern economy. The…
ClassificationFormTopic ClassificationPolyglot Prompt: Multilingual Multitask PrompTraining
This paper aims for a potential architectural improvement for multilingual learning and asks: Can different tasks from different languages be modeled in a monolithic framework, i.e. without any task/language-specific mod…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Natural Language Inference+5Label Semantic Aware Pre-training for Few-shot Text Classification
In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction.…
ClassificationFew-Shot Text ClassificationSentencetext-classification+2Multi-label topic classification for COVID-19 literature with Bioformer
We describe Bioformer team's participation in the multi-label topic classification task for COVID-19 literature (track 5 of BioCreative VII). Topic classification is performed using different BERT models (BioBERT, PubMed…
ArticlesClassificationSentenceSentence-Pair Classification+1Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning
Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks for both high-resourced and low-resourced languages. However, there is still a large performance drop f…
Cross-Lingual TransferLanguage ModellingNERparameter-efficient fine-tuning+6Prototypical Verbalizer for Prompt-based Few-shot Tuning
Prompt-based tuning for pre-trained language models (PLMs) has shown its effectiveness in few-shot learning. Typically, prompt-based tuning wraps the input text into a cloze question. To make predictions, the model maps …
Contrastive LearningEntity TypingFew-Shot LearningTopic ClassificationUnsupervised Keyphrase Extraction via Interpretable Neural Networks
Keyphrase extraction aims at automatically extracting a list of "important" phrases representing the key concepts in a document. Prior approaches for unsupervised keyphrase extraction resorted to heuristic notions of phr…
ArticlesKeyphrase ExtractionTopic ClassificationRealistic Zero-Shot Cross-Lingual Transfer in Legal Topic Classification
We consider zero-shot cross-lingual transfer in legal topic classification using the recent Multi-EURLEX dataset. Since the original dataset contains parallel documents, which is unrealistic for zero-shot cross-lingual t…
ClassificationCross-Lingual TransferTopic ClassificationTranslation+1Unlearnable Text for Neural Classifiers
Neural text classification models are known to001explore statistical patterns during supervised002learning. However, such patterns include spurious patterns and superficial regularity in the004training data. In this …
ClassificationGender Classificationtext-classificationText Classification+1Zero-Shot Cross-Lingual Transfer in Legal Domain Using Transformer Models
Zero-shot cross-lingual transfer is an important feature in modern NLP models and architectures to support low-resource languages. In this work, We study zero-shot cross-lingual transfer from English to French and German…
ClassificationCross-Lingual TransferLanguage ModelingLanguage Modelling+6A Multilingual Bag-of-Entities Model for Zero-Shot Cross-Lingual Text Classification
We present a multilingual bag-of-entities model that effectively boosts the performance of zero-shot cross-lingual text classification by extending a multilingual pre-trained language model (e.g., M-BERT). It leverages t…
ClassificationEntity TypingLanguage ModelingLanguage Modelling+3