# Meeting Decision Tracker: Making Meeting Minutes with De-Contextualized Utterances

arXiv: https://arxiv.org/abs/2210.11374 · HTML: https://mlsanity.com/paper/2210.11374/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 22 references that are in the map.
- First posted on arXiv 20 Oct 2022.

## Builds on (most cited first, 12 of 12)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://mlsanity.com/paper/1905.03197/) (2019)
- [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://mlsanity.com/paper/2001.04063/) (2020)
- [Improving Multi-turn Dialogue Modelling with Utterance ReWriter](https://mlsanity.com/paper/1906.07004/) (2019)
- [Pretrained Language Models for Sequential Sentence Classification](https://mlsanity.com/paper/1909.04054/) (2019)
- [Incomplete Utterance Rewriting as Semantic Segmentation](https://mlsanity.com/paper/2009.13166/) (2020)
- [SARG: A Novel Semi Autoregressive Generator for Multi-turn Incomplete Utterance Restoration](https://mlsanity.com/paper/2008.01474/) (2020)
- [Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation](https://mlsanity.com/paper/2204.03958/) (2022)
- [Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks](https://mlsanity.com/paper/1805.10390/) (2018)
- [s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning](https://mlsanity.com/paper/2110.13640/) (2021)
- [Discussion Tracker: Supporting Teacher Learning about Students' Collaborative Argumentation in High School Classrooms](https://mlsanity.com/paper/2102.10293/) (2021)

## Abstract (arXiv)

Meetings are a universal process to make decisions in business and project collaboration. The capability to automatically itemize the decisions in daily meetings allows for extensive tracking of past discussions. To that end, we developed Meeting Decision Tracker, a prototype system to construct decision items comprising decision utterance detector (DUD) and decision utterance rewriter (DUR). We show that DUR makes a sizable contribution to improving the user experience by dealing with utterance collapse in natural conversation. An introduction video of our system is also available at https://youtu.be/TG1pJJo0Iqo.