Papers by Sajad Sotudeh

3 papers
Learning to Rank Salient Content for Query-focused Summarization (2024.emnlp-main)

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Challenge: Query-focused summarization (QFS) is gaining prominence in research community.
Approach: They propose to integrate Learning-to-Rank (LTR) with Query-focused Summarization (QFS) to enhance the summary relevance via content prioritization.
Outcome: The proposed model outperforms the state-of-the-art on QMSum benchmark and SQuALITY benchmark while offering a lower training overhead.
TSTR: Too Short to Represent, Summarize with Details! Intro-Guided Extended Summary Generation (2022.naacl-main)

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Challenge: Existing methods for extractive and abstract summarization are limited to short abstracts . however, extended summaries provide detailed information beyond coarse information .
Approach: They propose an extractive summarization tool that utilizes the introductory information of documents as pointers to their salient information.
Outcome: The proposed extractive summarization improves on existing datasets with human-written summaries . the proposed summarizing improves in terms of cohesion and completeness compared to baselines and state-of-the-art .
MentSum: A Resource for Exploring Summarization of Mental Health Online Posts (2022.lrec-1)

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Challenge: Mental health remains a significant challenge of public health worldwide . many use online platforms to share their mental health conditions and seek help .
Approach: They analyze a dataset of over 24k user posts from Reddit and 43 mental health subreddits to generate a short summarization.
Outcome: The proposed dataset compared over 24k user posts and 43 mental health subreddits . it shows that the summarization of these posts is faster and more accurate than previous studies.

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