Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Prompted Contextual Vectors for Spear-Phishing Detection
Spear-phishing attacks present a significant security challenge, with large language models (LLMs) escalating the threat by generating convincing emails and facilitating target reconnaissance. To address this, we propose…
Document ClassificationNLP for Knowledge Discovery and Information Extraction from Energetics Corpora
We present a demonstration of the utility of NLP for aiding research into energetic materials and associated systems. The NLP method enables machine understanding of textual data, offering an automated route to knowledge…
ArticlesDocument ClassificationLanguage ModelingLanguage ModellingEfficient Models for the Detection of Hate, Abuse and Profanity
Large Language Models (LLMs) are the cornerstone for many Natural Language Processing (NLP) tasks like sentiment analysis, document classification, named entity recognition, question answering, summarization, etc. LLMs a…
Document Classificationnamed-entity-recognitionNamed Entity RecognitionQuestion Answering+1Generalized Sobolev Transport for Probability Measures on a Graph
We study the optimal transport (OT) problem for measures supported on a graph metric space. Recently, Le et al. (2022) leverage the graph structure and propose a variant of OT, namely Sobolev transport (ST), which yields…
Document ClassificationTopological Data AnalysisANLS* -- A Universal Document Processing Metric for Generative Large Language Models
Traditionally, discriminative models have been the predominant choice for tasks like document classification and information extraction. These models make predictions that fall into a limited number of predefined classes…
Document ClassificationL3Cube-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+4GeoGalactica: A Scientific Large Language Model in Geoscience
Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their impressive abilities, LLMs have shed li…
Document ClassificationGeneral KnowledgeLanguage ModelingLanguage Modelling+4A Learning oriented DLP System based on Classification Model
Data is the key asset for organizations and data sharing is lifeline for organization growth; which may lead to data loss. Data leakage is the most critical issue being faced by organizations. In order to mitigate the da…
ClassificationDocument ClassificationDiversifying Knowledge Enhancement of Biomedical Language Models using Adapter Modules and Knowledge Graphs
Recent advances in natural language processing (NLP) owe their success to pre-training language models on large amounts of unstructured data. Still, there is an increasing effort to combine the unstructured nature of LMs…
Document ClassificationKnowledge GraphsNatural Language InferenceQuestion AnsweringMELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRA
Large language models (LLMs) have shown great success in various Natural Language Processing (NLP) tasks, whist they still need updates after deployment to fix errors or keep pace with the changing knowledge in the world…
Document ClassificationHallucinationModel EditingQuestion AnsweringLarge language models in healthcare and medical domain: A review
The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable capability to provide proficient responses to free-text querie…
Document Classificationnamed-entity-recognitionNamed Entity RecognitionNatural Language Inference+2Summarization-based Data Augmentation for Document Classification
Despite the prevalence of pretrained language models in natural language understanding tasks, understanding lengthy text such as document is still challenging due to the data sparseness problem. Inspired by that humans d…
ClassificationData AugmentationDocument ClassificationNatural Language UnderstandingSUT: a new multi-purpose synthetic dataset for Farsi document image analysis
This paper introduces a new large-scale dataset for Farsi document images, named SUT, which aims to tackle the challenges associated with obtaining diverse and substantial ground-truth data for supervised models in docum…
Document Classificationdocument-image-classificationDocument Image Classificationimage-classification+5Learning Section Weights for Multi-Label Document Classification
Multi-label document classification is a traditional task in NLP. Compared to single-label classification, each document can be assigned multiple classes. This problem is crucially important in various domains, such as t…
ArticlesClassificationDocument ClassificationMulti-Label Classification+1Causality is all you need
In the fundamental statistics course, students are taught to remember the well-known saying: "Correlation is not Causation". Till now, statistics (i.e., correlation) have developed various successful frameworks, such as …
AllDocument ClassificationATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science
Large language models record impressive performance on many natural language processing tasks. However, their knowledge capacity is limited to the pretraining corpus. Retrieval augmentation offers an effective solution b…
Document ClassificationGraph Neural NetworkLanguage ModelingLanguage Modelling+3ContraDoc: Understanding Self-Contradictions in Documents with Large Language Models
In recent times, large language models (LLMs) have shown impressive performance on various document-level tasks such as document classification, summarization, and question-answering. However, research on understanding t…
Document ClassificationQuestion AnsweringExplainable Text Classification Techniques in Legal Document Review: Locating Rationales without Using Human Annotated Training Text Snippets
US corporations regularly spend millions of dollars reviewing electronically-stored documents in legal matters. Recently, attorneys apply text classification to efficiently cull massive volumes of data to identify respon…
Document Classificationtext-classificationText ClassificationEnhancing Document Information Analysis with Multi-Task Pre-training: A Robust Approach for Information Extraction in Visually-Rich Documents
This paper introduces a deep learning model tailored for document information analysis, emphasizing document classification, entity relation extraction, and document visual question answering. The proposed model leverage…
AllDocument ClassificationQuestion AnsweringRelation Extraction+1A Multi-Modal Multilingual Benchmark for Document Image Classification
Document image classification is different from plain-text document classification and consists of classifying a document by understanding the content and structure of documents such as forms, emails, and other such docu…
ClassificationCross-Lingual TransferDocument AIDocument Classification+8