Papers Topic Classification
“Topic Classification” 태그가 달린 논문 186편 · 필터 해제
A Soft Contrastive Learning-based Prompt Model for Few-shot Sentiment Analysis
Few-shot text classification has attracted great interest in both academia and industry due to the lack of labeled data in many fields. Different from general text classification (e.g., topic classification), few-shot se…
ClassificationContrastive LearningFew-Shot Text ClassificationSentiment Analysis+4DRAFT: Dense Retrieval Augmented Few-shot Topic classifier Framework
With the growing volume of diverse information, the demand for classifying arbitrary topics has become increasingly critical. To address this challenge, we introduce DRAFT, a simple framework designed to train a classifi…
ClassificationIn-Context LearningRetrievalTopic ClassificationNLEBench+NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian
Norwegian, spoken by only 5 million population, is under-representative within the most impressive breakthroughs in NLP tasks. To the best of our knowledge, there has not yet been a comprehensive evaluation of the existi…
Natural Language UnderstandingQuestion AnsweringText GenerationTopic ClassificationHow good are Large Language Models on African Languages?
Recent advancements in natural language processing have led to the proliferation of large language models (LLMs). These models have been shown to yield good performance, using in-context learning, even on tasks and langu…
In-Context LearningLanguage ModellingMachine Translationnamed-entity-recognition+6Attention-Enhancing Backdoor Attacks Against BERT-based Models
Recent studies have revealed that \textit{Backdoor Attacks} can threaten the safety of natural language processing (NLP) models. Investigating the strategies of backdoor attacks will help to understand the model's vulner…
Sentiment AnalysisTopic ClassificationIn-Context Learning with Iterative Demonstration Selection
Spurred by advancements in scale, large language models (LLMs) have demonstrated strong few-shot learning ability via in-context learning (ICL). However, the performance of ICL has been shown to be highly sensitive to th…
Few-Shot LearningIn-Context LearningQuestion AnsweringSentiment Analysis+1Domain-Specific Language Model Post-Training for Indonesian Financial NLP
BERT and IndoBERT have achieved impressive performance in several NLP tasks. There has been several investigation on its adaption in specialized domains especially for English language. We focus on financial domain and I…
Language ModelingLanguage ModellingSentiment AnalysisTopic ClassificationHuBERTopic: Enhancing Semantic Representation of HuBERT through Self-supervision Utilizing Topic Model
Recently, the usefulness of self-supervised representation learning (SSRL) methods has been confirmed in various downstream tasks. Many of these models, as exemplified by HuBERT and WavLM, use pseudo-labels generated fro…
Automatic Speech RecognitionRepresentation Learningspeech-recognitionSpeech Recognition+1UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers
Conspiracy theories have become a prominent and concerning aspect of online discourse, posing challenges to information integrity and societal trust. As such, we address conspiracy theory detection as proposed by the ACT…
Binary ClassificationClassificationData AugmentationSentence+1Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence
The increasing capacities of large language models (LLMs) have been shown to present an unprecedented opportunity to scale up data analytics in the humanities and social sciences, by automating complex qualitative tasks …
BenchmarkingChange DetectionImputationTopic ClassificationSIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects
Despite the progress we have recorded in the last few years in multilingual natural language processing, evaluation is typically limited to a small set of languages with available datasets which excludes a large number o…
Cross-Lingual TransferLanguage ModellingLarge Language ModelMachine Translation+3Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens
Many useful tasks on scientific documents, such as topic classification and citation prediction, involve corpora that span multiple scientific domains. Typically, such tasks are accomplished by representing the text with…
Citation PredictionTopic ClassificationBenchmarking Multilabel Topic Classification in the Kyrgyz Language
Kyrgyz is a very underrepresented language in terms of modern natural language processing resources. In this work, we present a new public benchmark for topic classification in Kyrgyz, introducing a dataset based on coll…
BenchmarkingClassificationNews ClassificationTopic ClassificationAmerican Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers
Existing full text datasets of U.S. public domain newspapers do not recognize the often complex layouts of newspaper scans, and as a result the digitized content scrambles texts from articles, headlines, captions, advert…
ArticlesLanguage ModelingLanguage ModellingLarge Language Model+3MetRoBERTa: Leveraging Traditional Customer Relationship Management Data to Develop a Transit-Topic-Aware Language Model
Transit riders' feedback provided in ridership surveys, customer relationship management (CRM) channels, and in more recent times, through social media is key for transit agencies to better gauge the efficacy of their se…
Language ModelingLanguage ModellingLarge Language ModelManagement+1vONTSS: vMF based semi-supervised neural topic modeling with optimal transport
Recently, Neural Topic Models (NTM), inspired by variational autoencoders, have attracted a lot of research interest; however, these methods have limited applications in the real world due to the challenge of incorporati…
ClassificationDiversitytext-classificationText Classification+2Towards Open-Domain Topic Classification
We introduce an open-domain topic classification system that accepts user-defined taxonomy in real time. Users will be able to classify a text snippet with respect to any candidate labels they want, and get instant respo…
ClassificationLanguage ModelingLanguage ModellingTopic ClassificationMultilingual Few-Shot Learning via Language Model Retrieval
Transformer-based language models have achieved remarkable success in few-shot in-context learning and drawn a lot of research interest. However, these models' performance greatly depends on the choice of the example pro…
Few-Shot LearningIn-Context LearningIntent DetectionLanguage Modeling+6Monolingual and Cross-Lingual Knowledge Transfer for Topic Classification
This article investigates the knowledge transfer from the RuQTopics dataset. This Russian topical dataset combines a large sample number (361,560 single-label, 170,930 multi-label) with extensive class coverage (76 class…
ClassificationTopic ClassificationTransfer LearningIzindaba-Tindzaba: Machine learning news categorisation for Long and Short Text for isiZulu and Siswati
Local/Native South African languages are classified as low-resource languages. As such, it is essential to build the resources for these languages so that they can benefit from advances in the field of natural language p…
ClassificationregressionTopic ClassificationWord Embeddings