Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
End-to-End Document Classification and Key Information Extraction using Assignment Optimization
We propose end-to-end document classification and key information extraction (KIE) for automating document processing in forms. Through accurate document classification we harness known information from templates to enha…
ClassificationDocument ClassificationKey Information ExtractionGVdoc: Graph-based Visual Document Classification
The robustness of a model for real-world deployment is decided by how well it performs on unseen data and distinguishes between in-domain and out-of-domain samples. Visual document classifiers have shown impressive perfo…
ClassificationDocument ClassificationGraph AttentionGraph Neural Network+2Neural Natural Language Processing for Long Texts: A Survey on Classification and Summarization
The adoption of Deep Neural Networks (DNNs) has greatly benefited Natural Language Processing (NLP) during the past decade. However, the demands of long document analysis are quite different from those of shorter texts, …
Document ClassificationDocument SummarizationManagementSentiment AnalysisDUBLIN -- Document Understanding By Language-Image Network
Visual document understanding is a complex task that involves analyzing both the text and the visual elements in document images. Existing models often rely on manual feature engineering or domain-specific pipelines, whi…
Document Classificationdocument understandingFeature EngineeringKey Information Extraction+6CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic Modeling
Most existing topic models rely on bag-of-words (BOW) representation, which limits their ability to capture word order information and leads to challenges with out-of-vocabulary (OOV) words in new documents. Contextualiz…
Document ClassificationLanguage ModellingNatural Language UnderstandingNER+3DLUE: Benchmarking Document Language Understanding
Understanding documents is central to many real-world tasks but remains a challenging topic. Unfortunately, there is no well-established consensus on how to comprehensively evaluate document understanding abilities, whic…
BenchmarkingDocument Classificationdocument understandingA General-Purpose Multilingual Document Encoder
Massively multilingual pretrained transformers (MMTs) have tremendously pushed the state of the art on multilingual NLP and cross-lingual transfer of NLP models in particular. While a large body of work leveraged MMTs to…
Cross-Lingual TransferDocument ClassificationLong-range modelingMultilingual NLP+2Benchmarking large language models for biomedical natural language processing applications and recommendations
The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown…
BenchmarkingDocument ClassificationMedical Question Answeringnamed-entity-recognition+7HiPool: Modeling Long Documents Using Graph Neural Networks
Encoding long sequences in Natural Language Processing (NLP) is a challenging problem. Though recent pretraining language models achieve satisfying performances in many NLP tasks, they are still restricted by a pre-defin…
Document ClassificationSentenceLeveraging BERT Language Model for Arabic Long Document Classification
Given the number of Arabic speakers worldwide and the notably large amount of content in the web today in some fields such as law, medicine, or even news, documents of considerable length are produced regularly. Classify…
ClassificationDocument ClassificationLanguage ModelingLanguage ModellingA New Information Theory of Certainty for Machine Learning
Claude Shannon coined entropy to quantify the uncertainty of a random distribution for communication coding theory. We observe that the uncertainty nature of entropy also limits its direct usage in mathematical modeling.…
Document ClassificationHeRo: RoBERTa and Longformer Hebrew Language Models
In this paper, we fill in an existing gap in resources available to the Hebrew NLP community by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained language model HeRo for standar…
Document ClassificationLanguage ModelingLanguage Modellingnamed-entity-recognition+3Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding
Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations th…
Document Classificationnamed-entity-recognitionNamed Entity RecognitionNatural Language Inference+4Disentangling Structure and Style: Political Bias Detection in News by Inducing Document Hierarchy
We address an important gap in detecting political bias in news articles. Previous works that perform document classification can be influenced by the writing style of each news outlet, leading to overfitting and limited…
ArticlesBias DetectionDocument ClassificationSentenceA semi-automatic method for document classification in the shipping industry
In the shipping industry, document classification plays a crucial role in ensuring that the necessary documents are properly identified and processed for customs clearance. OCR technology is being used to automate the pr…
ClassificationDocument ClassificationOptical Character Recognition (OCR)Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifiers
Long-sequence transformers are designed to improve the representation of longer texts by language models and their performance on downstream document-level tasks. However, not much is understood about the quality of toke…
Document ClassificationLanguage ModelingLanguage ModellingSentence+2Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling
We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in a wide variety of fields, such as docume…
Document ClassificationElementwise Language Representation
We propose a new technique for computational language representation called elementwise embedding, in which a material (semantic unit) is abstracted into a horizontal concatenation of lower-dimensional element (character…
Document ClassificationSpecificityMatKB: Semantic Search for Polycrystalline Materials Synthesis Procedures
In this paper, we present a novel approach to knowledge extraction and retrieval using Natural Language Processing (NLP) techniques for material science. Our goal is to automatically mine structured knowledge from millio…
ArticlesDocument ClassificationRetrievalBioformer: an efficient transformer language model for biomedical text mining
Pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) have achieved state-of-the-art performance in natural language processing (NLP) tasks. Recently, BERT has been adapted to …
ArticlesDocument ClassificationLanguage ModelingLanguage Modelling+5