no code implementations • sdp (COLING) 2022 • Sajad Sotudeh, Nazli Goharian
This paper presents our approach for the MuP 2022 shared task —-Multi-Perspective Scientific Document Summarization, where the objective is to enable summarization models to explore methods for generating multi-perspective summaries for scientific papers.
no code implementations • 1 Nov 2024 • Sajad Sotudeh, Nazli Goharian
Compared to the state-of-the-art, our model outperforms on QMSum benchmark (all metrics) and matches on SQuALITY benchmark (2 metrics) as measured by Rouge and BertScore while offering a lower training overhead.
no code implementations • 14 Jul 2023 • Sajad Sotudeh, Nazli Goharian
Query-focused summarization (QFS) is a challenging task in natural language processing that generates summaries to address specific queries.
no code implementations • 2 Feb 2023 • Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt, Nazli Goharian
Recent Transformer-based summarization models have provided a promising approach to abstractive summarization.
no code implementations • 2 Feb 2023 • Sajad Sotudeh, Nazli Goharian, Hanieh Deilamsalehy, Franck Dernoncourt
Automatically generating short summaries from users' online mental health posts could save counselors' reading time and reduce their fatigue so that they can provide timely responses to those seeking help for improving their mental state.
no code implementations • LREC 2022 • Sajad Sotudeh, Nazli Goharian, Zachary Young
Some of these platforms, such as Reachout, are dedicated forums where the users register to seek help.
Ranked #1 on Text Summarization on MentSum
2 code implementations • NAACL 2022 • Sajad Sotudeh, Nazli Goharian
The recent interest to tackle this problem motivated curation of scientific datasets, arXiv-Long and PubMed-Long, containing human-written summaries of 400-600 words, hence, providing a venue for research in generating long/extended summaries.
1 code implementation • EMNLP (newsum) 2021 • Sajad Sotudeh, Hanieh Deilamsalehy, Franck Dernoncourt, Nazli Goharian
Recent models in developing summarization systems consist of millions of parameters and the model performance is highly dependent on the abundance of training data.
Ranked #1 on Extreme Summarization on TLDR9+
1 code implementation • 28 Dec 2020 • Sajad Sotudeh, Arman Cohan, Nazli Goharian
We then present our results on three long summarization datasets, arXiv-Long, PubMed-Long, and Longsumm.
Ranked #1 on Extended Summarization on arXiv-Long Test
no code implementations • SEMEVAL 2020 • Sajad Sotudeh, Tong Xiang, Hao-Ren Yao, Sean MacAvaney, Eugene Yang, Nazli Goharian, Ophir Frieder
Offensive language detection is an important and challenging task in natural language processing.
no code implementations • ACL 2020 • Sajad Sotudeh, Nazli Goharian, Ross W. Filice
Sequence-to-sequence (seq2seq) network is a well-established model for text summarization task.
no code implementations • 14 May 2019 • Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish Talati, Ross W. Filice
Automatically generating accurate summaries from clinical reports could save a clinician's time, improve summary coverage, and reduce errors.