Domain adaptation with pre-trained transformers for query-focused abstractive text summarization
Abstract 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 …
generate the summary of the text document (s) based on the given query. A key challenge in …
Can large language models fix data annotation errors? an empirical study using debatepedia for query-focused text summarization
Debatepedia is a publicly available dataset consisting of arguments and counter-arguments
on controversial topics that has been widely used for the single-document query-focused …
on controversial topics that has been widely used for the single-document query-focused …
CQSumDP: a ChatGPT-annotated resource for query-focused abstractive summarization based on debatepedia
Debatepedia is a publicly available dataset consisting of arguments and counter-arguments
on controversial topics that has been widely used for the single-document query-focused …
on controversial topics that has been widely used for the single-document query-focused …
Document summarization with latent queries
The availability of large-scale datasets has driven the development of neural models that
create generic summaries for single or multiple documents. For query-focused …
create generic summaries for single or multiple documents. For query-focused …
Surveying the landscape of text summarization with deep learning: A comprehensive review
In recent years, deep learning has revolutionized natural language processing (NLP) by
enabling the development of models that can learn complex representations of language …
enabling the development of models that can learn complex representations of language …
Domain Adaptation and Summary Distillation for Unsupervised Query Focused Summarization
J Du, Y Gao - IEEE Transactions on Knowledge and Data …, 2023 - ieeexplore.ieee.org
Text summarizing is the task of reducing a document's length while maintaining its essential
information. In the age of information explosion, how to obtain the content that users needed …
information. In the age of information explosion, how to obtain the content that users needed …
Text summarization with latent queries
The availability of large-scale datasets has driven the development of neural models that
create summaries from single documents, for generic purposes. When using a …
create summaries from single documents, for generic purposes. When using a …
ReQuEST: A small-scale multi-task model for community question-answering systems
The burgeoning popularity of community question-answering platforms as an information-
seeking strategy has prompted researchers to look for ways to save response time and …
seeking strategy has prompted researchers to look for ways to save response time and …
Generating Query Focused Summaries without Fine-tuning the Transformer-based Pre-trained Models
Fine-tuning the Natural Language Processing (NLP) models for each new data set requires
higher computational time associated with increased carbon footprint and cost. However …
higher computational time associated with increased carbon footprint and cost. However …
Query-Based Extractive Text Summarization Using Sense-Oriented Semantic Relatedness Measure
This paper presents a query-based extractive text summarization approach by using sense-
oriented semantic relatedness measure. To find the query relevant sentences, we have to …
oriented semantic relatedness measure. To find the query relevant sentences, we have to …