no code implementations • EACL (HCINLP) 2021 • Tatiana Passali, Alexios Gidiotis, Efstathios Chatzikyriakidis, Grigorios Tsoumakas
In order to overcome these issues, we reconsider the task of summarization from a human-centered perspective.
no code implementations • EMNLP (sdp) 2020 • Alexios Gidiotis, Stefanos Stefanidis, Grigorios Tsoumakas
We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020.
no code implementations • 9 Oct 2021 • 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.
no code implementations • Findings (ACL) 2022 • 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.
1 code implementation • 13 Apr 2020 • Alexios Gidiotis, Grigorios Tsoumakas
With this approach we can decompose the problem of long document summarization into smaller and simpler problems, reducing computational complexity and creating more training examples, which at the same time contain less noise in the target summaries compared to the standard approach.
Ranked #13 on Text Summarization on Pubmed (using extra training data)
1 code implementation • 19 May 2019 • 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.