5 papers
DUAL: Diversity and Uncertainty Active Learning for Text Summarization
Petros Stylianos Giouroukis, Alexios Gidiotis, Grigorios Tsoumakas
With the rise of large language models, neural text summarization has advanced significantly in recent years. However, even state-of-the-art models continue to rely heavily on high…
Bayesian Active Summarization
Alexios Gidiotis, Grigorios Tsoumakas
Bayesian Active Learning has had significant impact to various NLP problems, but nevertheless it's application to text summarization has been explored very little. We introduce Bay…
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue
Alexios Gidiotis, Grigorios Tsoumakas
We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning. Our approach approximates Bayesian infere…
A Divide-and-Conquer Approach to the Summarization of Long Documents
Alexios Gidiotis, Grigorios Tsoumakas
We present a novel divide-and-conquer method for the neural summarization of long documents. Our method exploits the discourse structure of the document and uses sentence similarit…
Structured Summarization of Academic Publications
Alexios Gidiotis, Grigorios Tsoumakas
We propose SUSIE, a novel summarization method that can work with state-of-the-art summarization models in order to produce structured scientific summaries for academic articles. W…