# Summaries, Highlights, and Action items: Design, implementation and evaluation of an LLM-powered meeting recap system

arXiv: https://arxiv.org/abs/2307.15793 · HTML: https://mlsanity.com/paper/2307.15793/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 113 references that are in the map.
- First posted on arXiv 28 Jul 2023.

## Builds on (most cited first, 18 of 18)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://mlsanity.com/paper/2006.03654/) (2020)
- [SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization](https://mlsanity.com/paper/1911.12237/) (2019)
- [DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://mlsanity.com/paper/2105.06762/) (2021)
- [A Survey on Dialogue Systems: Recent Advances and New Frontiers](https://mlsanity.com/paper/1711.01731/) (2017)
- [Text Summarization Techniques: A Brief Survey](https://mlsanity.com/paper/1707.02268/) (2017)
- [Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes](https://mlsanity.com/paper/1904.09612/) (2019)
- [Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization](https://mlsanity.com/paper/2208.09770/) (2022)
- [Investigation of End-To-End Speaker-Attributed ASR for Continuous Multi-Talker Recordings](https://mlsanity.com/paper/2008.04546/) (2020)
- [An Exploratory Study on Long Dialogue Summarization: What Works and What's Next](https://mlsanity.com/paper/2109.04609/) (2021)
- [Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems](https://mlsanity.com/paper/2001.04879/) (2020)
- [A Sliding-Window Approach to Automatic Creation of Meeting Minutes](https://mlsanity.com/paper/2104.12324/) (2021)
- [A Bag of Tricks for Dialogue Summarization](https://mlsanity.com/paper/2109.08232/) (2021)
- [User-Driven Research of Medical Note Generation Software](https://mlsanity.com/paper/2205.02549/) (2022)
- [Abstractive Meeting Summarization: A Survey](https://mlsanity.com/paper/2208.04163/) (2022)
- [A Survey on Neural Network-Based Summarization Methods](https://mlsanity.com/paper/1804.04589/) (2018)
- [Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions](https://mlsanity.com/paper/2210.09894/) (2022)

## Built on by (most cited first, 12 of 12)

- [H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions](https://mlsanity.com/paper/2606.09461/) (2026)
- [Summarizing Speech: A Comprehensive Survey](https://mlsanity.com/paper/2504.08024/) (2025)
- [Collaborative Document Editing with Multiple Users and AI Agents](https://mlsanity.com/paper/2509.11826/) (2025)
- [MeetMap: Real-Time Collaborative Dialogue Mapping with LLMs in Online Meetings](https://mlsanity.com/paper/2502.01564/) (2025)
- [MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf](https://mlsanity.com/paper/2502.04376/) (2025)
- [CHOIR: A Chatbot-mediated Organizational Memory Leveraging Communication in University Research Labs](https://mlsanity.com/paper/2509.20512/) (2025)
- [User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive Scenarios](https://mlsanity.com/paper/2510.20721/) (2025)
- [GVR-Coder: A Visual-Feedback Framework for Structured SVG Generation in Complex Document and Meeting Scenarios](https://mlsanity.com/paper/2607.28073/) (2026)
- [INTERACT: An AI-Driven Extended Reality Framework for Accesible Communication Featuring Real-Time Sign Language Interpretation and Emotion Recognition](https://mlsanity.com/paper/2604.05605/) (2026)
- [Summarization is Not Dead Yet](https://mlsanity.com/paper/2606.08000/) (2026)
- [Designing AI-Supported Focus Groups: A Role x Modality Playbook](https://mlsanity.com/paper/2606.11835/) (2026)
- [Speak for Me: Giving LLMs the Situational Awareness to Participate in a Meeting](https://mlsanity.com/paper/2609.03923/) (2026)

## Abstract (arXiv)

Meetings play a critical infrastructural role in coordinating work. The recent surge of hybrid and remote meetings in computer-mediated spaces has led to new problems (e.g., more time spent in less engaging meetings) and new opportunities (e.g., automated transcription/captioning and recap support). Advances in dialogue summarization offer the potential for improving post-meeting experiences, but fixed-length summaries often fail to meet diverse needs, such as quick overviews or detailed insights. To address these gaps, we use cognitive science and discourse theories to conceptualize two recap designs: important highlights and a structured, hierarchical minutes view, targeting complementary recap needs. We operationalize these representations into high-fidelity prototypes using dialogue summarization. Finally, we evaluate the representations' effectiveness with seven users in the context of their work meetings at Microsoft. Our results show both recap types are valuable in different contexts, enabling collaboration through discussions and consensus-building. Exploring the meaning of users adding, editing, and deleting from recaps suggests varying alignment for using these actions to improve AI-recap. Our design implications, such as incorporating organizational artifacts (e.g., linking presentations) in recaps and personalizing context, advance the discourse of effective recap designs for organizational work and support past results from cognition studies.