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        <title>Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion</title>
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    <abstract>We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs. Starting from well-founded assumptions about word graphs, we present simple but reliable path-reranking and topic segmentation schemes. Robustness of our method is demonstrated on datasets across multiple domains, including meetings, interviews, movie scripts, and day-to-day conversations. We also identify possible avenues to augment our heuristic-based system with deep learning. We open-source our code, to provide a strong, reproducible baseline for future research into unsupervised dialogue summarization.</abstract>
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%0 Conference Proceedings
%T Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion
%A Park, Seongmin
%A Lee, Jihwa
%Y Hruschka, Estevam
%Y Mitchell, Tom
%Y Mladenic, Dunja
%Y Grobelnik, Marko
%Y Bhutani, Nikita
%S Proceedings of the 2nd Workshop on Deriving Insights from User-Generated Text
%D 2022
%8 May
%I Association for Computational Linguistics
%C (Hybrid) Dublin, Ireland, and Virtual
%F park-lee-2022-unsupervised
%X We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs. Starting from well-founded assumptions about word graphs, we present simple but reliable path-reranking and topic segmentation schemes. Robustness of our method is demonstrated on datasets across multiple domains, including meetings, interviews, movie scripts, and day-to-day conversations. We also identify possible avenues to augment our heuristic-based system with deep learning. We open-source our code, to provide a strong, reproducible baseline for future research into unsupervised dialogue summarization.
%R 10.18653/v1/2022.wit-1.1
%U https://aclanthology.org/2022.wit-1.1
%U https://doi.org/10.18653/v1/2022.wit-1.1
%P 1-9

Markdown (Informal)

[Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion](https://aclanthology.org/2022.wit-1.1) (Park & Lee, WIT 2022)

• Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion (Park & Lee, WIT 2022)

ACL

• Seongmin Park and Jihwa Lee. 2022. Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion. In Proceedings of the 2nd Workshop on Deriving Insights from User-Generated Text, pages 1–9, (Hybrid) Dublin, Ireland, and Virtual. Association for Computational Linguistics.