Dialogue Summarization

Papers

DialogSum: A Real-Life Scenario Dialogue Summarization Dataset

https://arxiv.org/pdf/2105.06762v4.pdf

Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization

https://arxiv.org/pdf/2010.01672v1.pdf

Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization

https://arxiv.org/pdf/2109.04994v1.pdf

Controllable Abstractive Dialogue Summarization with Sketch Supervision

https://arxiv.org/pdf/2105.14064v2.pdf

Abstractive Dialogue Summarization with Sentence-Gated Modeling Optimized by Dialogue Acts

https://arxiv.org/pdf/1809.05715v2.pdf

Restructuring Conversations using Discourse Relations for Zero-shot Abstractive Dialogue Summarization

https://arxiv.org/pdf/1902.01615v2.pdf

Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph Networks

https://arxiv.org/pdf/2010.10044v1.pdf

Coreference-Aware Dialogue Summarization

https://arxiv.org/pdf/2106.08556v2.pdf

Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion

A Survey on Dialogue Summarization: Recent Advances and New Frontiers

https://arxiv.org/pdf/2107.03175.pdf

Post-Training Dialogue Summarization using Pseudo-Paraphrasing

https://arxiv.org/pdf/2204.13498.pdf

A FOCUSED STUDY ON SEQUENCE LENGTH FOR DIALOGUE SUMMARIZATION

https://arxiv.org/pdf/2209.11910v2.pdf

A Bag of Tricks for Dialogue Summarization

RepSum: Unsupervised Dialogue Summarization based on Replacement Strategy

An Exploratory Study on Long Dialogue Summarization: What Works and What’s Next

Summaries

Further Readings

Papers with Code - Abstractive Dialogue Summarization

To capture the various topic information of a conversation and outline salient facts for the captured topics, this work proposes two topic-aware contrastive learning objectives, namely coherence detection and sub-summary generation objectives, which are expected to implicitly model the topic change and handle information scattering challenges for the dialogue summarization task.

https://paperswithcode.com/task/abstractive-dialogue-summarization

Abstractive Summarization of Dialogues

" There are 2.5 quintillion bytes of data created each day " - That was 2017, and now we seem to have even lost the count. Putting things in a concise way has become very critical. No doubt, automation has reached the art of summarization.

https://medium.com/@saketdingliwal97/abstractive-summarization-of-dialogues-f530c7d290be

Dialogue Summarization: A Deep Learning Approach

Dialogue Summarization: Its types and methodology Image cc: Aseem Srivastava Humans are social animals, we exchange ideas, share information, and make plans with each other. Text and Speech are the two common conversation mediums, but mostly it's speech.

https://www.analyticsvidhya.com/blog/2021/02/dialogue-summarization-a-deep-learning-approach/