Papers Extractive Summarization
“Extractive Summarization” 태그가 달린 논문 315편 · 필터 해제
StrucSum: Graph-Structured Reasoning for Long Document Extractive Summarization with LLMs
Large language models (LLMs) have shown strong performance in zero-shot summarization, but often struggle to model document structure and identify salient information in long texts. In this work, we introduce StrucSum, a…
Extractive SummarizationSentenceSafeChat: A Framework for Building Trustworthy Collaborative Assistants and a Case Study of its Usefulness
Collaborative assistants, or chatbots, are data-driven decision support systems that enable natural interaction for task completion. While they can meet critical needs in modern society, concerns about their reliability …
ChatbotExtractive SummarizationInformation RetrievalLarge Language Model+1Advancements in Natural Language Processing for Automatic Text Summarization
The substantial growth of textual content in diverse domains and platforms has led to a considerable need for Automatic Text Summarization (ATS) techniques that aid in the process of text analysis. The effectiveness of t…
Abstractive Text SummarizationExtractive SummarizationText GenerationText SummarizationOrderSum: Semantic Sentence Ordering for Extractive Summarization
There are two main approaches to recent extractive summarization: the sentence-level framework, which selects sentences to include in a summary individually, and the summary-level framework, which generates multiple cand…
Extractive SummarizationSentenceSentence OrderingLotus: Creating Short Videos From Long Videos With Abstractive and Extractive Summarization
Short-form videos are popular on platforms like TikTok and Instagram as they quickly capture viewers' attention. Many creators repurpose their long-form videos to produce short-form videos, but creators report that plann…
Extractive SummarizationFormState Space Models for Extractive Summarization in Low Resource Scenarios
Extractive summarization involves selecting the most relevant sentences from a text. Recently, researchers have focused on advancing methods to improve state-of-the-art results in low-resource settings. Motivated by thes…
Extractive SummarizationMambaSentenceState Space ModelsCHIMA: Headline-Guided Extractive Summarization for Thai News Articles
Text summarization is a process of condensing lengthy texts while preserving their essential information. Previous studies have predominantly focused on high-resource languages, while low-resource languages like Thai hav…
ArticlesExtractive SummarizationSentenceText SummarizationA Novel Word Pair-based Gaussian Sentence Similarity Algorithm For Bengali Extractive Text Summarization
Extractive Text Summarization is the process of selecting the most representative parts of a larger text without losing any key information. Recent attempts at extractive text summarization in Bengali, either relied on s…
ArticlesExtractive SummarizationExtractive Text SummarizationSentence+2Multi-label Sequential Sentence Classification via Large Language Model
Sequential sentence classification (SSC) in scientific publications is crucial for supporting downstream tasks such as fine-grained information retrieval and extractive summarization. However, current SSC methods are con…
Contrastive LearningExtractive SummarizationIn-Context LearningInformation Retrieval+7Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare
This review examines the development of abstractive NLP-based text summarization approaches and compares them to existing techniques for extractive summarization. A brief history of text summarization from the 1950s to t…
Extractive SummarizationText SummarizationFair Summarization: Bridging Quality and Diversity in Extractive Summaries
Fairness in multi-document summarization of user-generated content remains a critical challenge in natural language processing (NLP). Existing summarization methods often fail to ensure equitable representation across di…
DiversityDocument SummarizationExtractive SummarizationFairness+1Video Summarization Techniques: A Comprehensive Review
The rapid expansion of video content across a variety of industries, including social media, education, entertainment, and surveillance, has made video summarization an essential field of study. The current work is a sur…
Abstractive Text SummarizationExtractive SummarizationVideo SummarizationAbstractive Summarization of Low resourced Nepali language using Multilingual Transformers
Automatic text summarization in Nepali language is an unexplored area in natural language processing (NLP). Although considerable research has been dedicated to extractive summarization, the area of abstractive summariza…
Abstractive Text SummarizationArticlesExtractive SummarizationHeadline Generation+2Scaling Up Summarization: Leveraging Large Language Models for Long Text Extractive Summarization
In an era where digital text is proliferating at an unprecedented rate, efficient summarization tools are becoming indispensable. While Large Language Models (LLMs) have been successfully applied in various NLP tasks, th…
Extractive SummarizationExtractive Text SummarizationLanguage ModelingLanguage Modelling+3Summarization of Investment Reports Using Pre-trained Model
In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on f…
Abstractive Text SummarizationExtractive SummarizationManagementmodelA Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches
Existing approaches for low-resource text summarization primarily employ large language models (LLMs) like GPT-3 or GPT-4 at inference time to generate summaries directly; however, such approaches often suffer from incon…
Abstractive Text SummarizationData AugmentationExtractive SummarizationExtractive Text Summarization+5Applicability of Large Language Models and Generative Models for Legal Case Judgement Summarization
Automatic summarization of legal case judgements, which are known to be long and complex, has traditionally been tried via extractive summarization models. In recent years, generative models including abstractive summari…
Abstractive Text SummarizationExtractive SummarizationTowards Enhancing Coherence in Extractive Summarization: Dataset and Experiments with LLMs
Extractive summarization plays a pivotal role in natural language processing due to its wide-range applications in summarizing diverse content efficiently, while also being faithful to the original content. Despite signi…
Extractive SummarizationLaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports
Citizen reporting platforms like Safe City in India help the public and authorities stay informed about sexual harassment incidents. However, the high volume of data shared on these platforms makes reviewing each individ…
Extractive SummarizationInstructCMP: Length Control in Sentence Compression through Instruction-based Large Language Models
Extractive summarization can produce faithful summaries but often requires additional constraints such as a desired summary length. Traditional sentence compression models do not typically consider the constraints becaus…
Extractive SummarizationSentenceSentence Compression