Search Results for author:
Found 6 papers, 2 papers with code
AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20
We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020.
Towards Human-Centered Summarization: A Case Study on Financial News
In order to overcome these issues, we reconsider the task of summarization from a human-centered perspective.
Bayesian Active Summarization
Bayesian Active Learning has had significant impact to various NLP problems, but nevertheless it's application to text summarization has been explored very little.
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue
We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning.
A Divide-and-Conquer Approach to the Summarization of Long Documents
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)
Structured Summarization of Academic Publications
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.
