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We advance the state-of-the-art in unsupervised abstractive dialoguesummarization by utilizing multi-sentence compression graphs. Starting fromwell-founded assumptions about word graphs, we present simple but reliablepath-reranking and topic segmentation schemes. Robustness of our method isdemonstrated on datasets across multiple domains, including meetings,interviews, movie scripts, and day-to-day conversations. We also identifypossible avenues to augment our heuristic-based system with deep learning. Weopen-source our code, to provide a strong, reproducible baseline for futureresearch into unsupervised dialogue summarization.

Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion