Papers Abstractive Text Summarization
“Abstractive Text Summarization” 태그가 달린 논문 852편 · 필터 해제
Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization
This paper presents Z-Code++, a new pre-trained language model optimized for abstractive text summarization. The model extends the state of the art encoder-decoder model using three techniques. First, we use a two-phase …
Abstractive Text SummarizationDecoderLanguage ModelingLanguage Modelling+2Abstractive Meeting Summarization: A Survey
A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service…
Abstractive Dialogue SummarizationAbstractive Text SummarizationDecoderMeeting Summarization+2Forming Trees with Treeformers
Human language is known to exhibit a nested, hierarchical structure, allowing us to form complex sentences out of smaller pieces. However, many state-of-the-art neural networks models such as Transformers have no explici…
Abstractive Text SummarizationInductive BiasMachine TranslationNatural Language Understanding+1Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation
Large pretrained language models (PLMs) are often domain- or task-adapted via fine-tuning or prompting. Finetuning requires modifying all of the parameters and having enough data to avoid overfitting while prompting requ…
Abstractive Text SummarizationLanguage ModelingLanguage ModellingMeta-LearningImproving the Faithfulness of Abstractive Summarization via Entity Coverage Control
Abstractive summarization systems leveraging pre-training language models have achieved superior results on benchmark datasets. However, such models have been shown to be more prone to hallucinate facts that are unfaithf…
Abstractive Text SummarizationSemantic-Preserving Abstractive Text Summarization with Siamese Generative Adversarial Net
We propose a novel siamese generative adversarial net for abstractive text summarization (SSPGAN), which can preserve the main semantics of the source text. Different from previous generative adversarial net based method…
Abstractive Text SummarizationText SummarizationJointly Learning Guidance Induction and Faithful Summary Generation via Conditional Variational Autoencoders
Abstractive summarization can generate high quality results with the development of the neural network. However, generating factual consistency summaries is a challenging task for abstractive summarization. Recent studie…
Abstractive Text SummarizationDACSA: A large-scale Dataset for Automatic summarization of Catalan and Spanish newspaper Articles
The application of supervised methods to automatic summarization requires the availability of adequate corpora consisting of a set of document-summary pairs. As in most Natural Language Processing tasks, the great majori…
Abstractive Text SummarizationArticlesBenchmarkingFew-shot fine-tuning SOTA summarization models for medical dialogues
Abstractive summarization of medical dialogues presents a challenge for standard training approaches, given the paucity of suitable datasets. We explore the performance of state-of-the-art models with zero-shot and few-s…
Abstractive Text SummarizationFew-Shot LearningMulti-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities
With the advent of large language models, methods for abstractive summarization have made great strides, creating potential for use in applications to aid knowledge workers processing unwieldy document collections. One s…
Abstractive Text SummarizationDocument SummarizationMulti-Document SummarizationSentence0/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92Indian Legal Text Summarization: A Text Normalisation-based Approach
In the Indian court system, pending cases have long been a problem. There are more than 4 crore cases outstanding. Manually summarising hundreds of documents is a time-consuming and tedious task for legal stakeholders. M…
Abstractive Text SummarizationText SummarizationDomain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization
The Query-Focused Text Summarization (QFTS) task aims at building systems that generate the summary of the text document(s) based on the given query. A key challenge in addressing this task is the lack of large labeled d…
Abstractive Text SummarizationDomain AdaptationText SummarizationTransfer Learning+1TeSum: Human-Generated Abstractive Summarization Corpus for Telugu
Expert human annotation for summarization is definitely an expensive task, and can not be done on huge scales. But with this work, we show that even with a crowd sourced summary generation approach, quality can be contro…
Abstractive Text SummarizationThe Bull and the Bear: Summarizing Stock Market Discussions
Stock market investors debate and heavily discuss stock ideas, investing strategies, news and market movements on social media platforms. The discussions are significantly longer in length and require extensive domain ex…
Abstractive Text SummarizationCATAMARAN: A Cross-lingual Long Text Abstractive Summarization Dataset
Cross-lingual summarization, which produces the summary in one language from a given source document in another language, could be extremely helpful for humans to obtain information across the world. However, it is still…
Abstractive Text SummarizationArticlesCross-Lingual Abstractive SummarizationMultilingual Text Summarization on Financial Documents
This paper proposes a multilingual Automated Text Summarization (ATS) method targeting the Financial Narrative Summarization Task (FNS-2022). We developed two systems; the first uses a pre-trained abstractive summarizati…
Abstractive Text SummarizationText SummarizationExtractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek
This paper describes the three summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS-2022). We developed a task-specific extractive summarization method for the reports in English. It …
Abstractive Text SummarizationDecoderExtractive SummarizationSentence+1Multilingual Financial Documentation Summarization by Team_Tredence for FNS2022
This paper describes multi-lingual long document summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS 2022 ) by Team-Tredence. We developed task-specific summarization methods for 3 l…
Abstractive Text SummarizationDocument SummarizationSemantic SimilaritySemantic Textual SimilarityUnderstanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors
The propensity of abstractive summarization models to make factual errors has been studied extensively, including design of metrics to detect factual errors and annotation of errors in current systems' outputs. However, …
Abstractive Text Summarization