The Role of Summarization in Generative Agents: A Preliminary Perspective
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
Generative agents that simulate human society show tremendous potential for further research and practical applications. Specifically, the generative agent architecture comprising several meticulously designed modules constitutes the most critical component. To facilitate progress in this research, this report presents our integrated perspective on comprehending generative agents through summarization, since we believe summarization is the most fundamental and indispensable capacity of generative agents manifested across diverse scenarios. We hope this report can provide insight into understanding the importance of summarization capacity in generative agents and motivate future research.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 8 of its 12 references that are in the map. First posted on arXiv 2 May 2023.
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- 2023A Survey of Large Language Modelscited by 2,537
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- 2023LLM as A Robotic Brain: Unifying Egocentric Memory and Controlcited by 32
- 2020Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarizationcited by 27
- 2020QURIOUS: Question Generation Pretraining for Text Generationcited by 12
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- 2025Do Large Language Models Solve the Problems of Agent-Based Modeling? A Critical Review of Generative Social Simulations