Search Results for author: Sajad Sotudeh

Found 11 papers, 3 papers with code

Ontology-Aware Clinical Abstractive Summarization

no code implementations14 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.

Abstractive Text Summarization

TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts

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.

Extreme Summarization Sentence

TSTR: Too Short to Represent, Summarize with Details! Intro-Guided Extended Summary Generation

1 code implementation 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.

Extended Summarization

Curriculum-guided Abstractive Summarization for Mental Health Online Posts

no code implementations2 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.

Abstractive Text Summarization Extreme Summarization +1

QontSum: On Contrasting Salient Content for Query-focused Summarization

no code implementations14 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.

Answer Generation Contrastive Learning +3

GUIR @ MuP 2022: Towards Generating Topic-aware Multi-perspective Summaries for Scientific Documents

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.

Document Summarization Scientific Document Summarization

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