@inproceedings{zhu-etal-2025-social,
title = "Social Intelligence in the Age of {LLM}s",
author = "Zhu, Hao and
Majumder, Bodhisattwa Prasad and
Hovy, Dirk and
Yang, Diyi",
editor = "Lomeli, Maria and
Swayamdipta, Swabha and
Zhang, Rui",
booktitle = "Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)",
month = may,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-tutorial.8/",
doi = "10.18653/v1/2025.naacl-tutorial.8",
pages = "51--55",
ISBN = "979-8-89176-193-3",
abstract = "With the emergence of Large Language Models (LLMs), we now have unprecedented opportunities to incorporate human-like communication and context-aware interactions into artificial systems. But what is the current state of LLMs' capability of social interaction? Can they truly understand social scenarios, perform social reasoning, or interact with humans as socially competent agents? We propose this tutorial as an introduction to and an overview of different aspects of artificial social intelligence and their relationship with LLMs. In this tutorial, we will explore these questions by introducing scientific methods for evaluating social intelligence in LLMs, highlighting the key challenges, and identifying promising research directions. Participants will not only gain a comprehensive overview of the field{'}s progress, but also acquire technical skills on analysing and developing LLM-based social intelligence."
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<abstract>With the emergence of Large Language Models (LLMs), we now have unprecedented opportunities to incorporate human-like communication and context-aware interactions into artificial systems. But what is the current state of LLMs’ capability of social interaction? Can they truly understand social scenarios, perform social reasoning, or interact with humans as socially competent agents? We propose this tutorial as an introduction to and an overview of different aspects of artificial social intelligence and their relationship with LLMs. In this tutorial, we will explore these questions by introducing scientific methods for evaluating social intelligence in LLMs, highlighting the key challenges, and identifying promising research directions. Participants will not only gain a comprehensive overview of the field’s progress, but also acquire technical skills on analysing and developing LLM-based social intelligence.</abstract>
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%0 Conference Proceedings
%T Social Intelligence in the Age of LLMs
%A Zhu, Hao
%A Majumder, Bodhisattwa Prasad
%A Hovy, Dirk
%A Yang, Diyi
%Y Lomeli, Maria
%Y Swayamdipta, Swabha
%Y Zhang, Rui
%S Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-193-3
%F zhu-etal-2025-social
%X With the emergence of Large Language Models (LLMs), we now have unprecedented opportunities to incorporate human-like communication and context-aware interactions into artificial systems. But what is the current state of LLMs’ capability of social interaction? Can they truly understand social scenarios, perform social reasoning, or interact with humans as socially competent agents? We propose this tutorial as an introduction to and an overview of different aspects of artificial social intelligence and their relationship with LLMs. In this tutorial, we will explore these questions by introducing scientific methods for evaluating social intelligence in LLMs, highlighting the key challenges, and identifying promising research directions. Participants will not only gain a comprehensive overview of the field’s progress, but also acquire technical skills on analysing and developing LLM-based social intelligence.
%R 10.18653/v1/2025.naacl-tutorial.8
%U https://aclanthology.org/2025.naacl-tutorial.8/
%U https://doi.org/10.18653/v1/2025.naacl-tutorial.8
%P 51-55
Markdown (Informal)
[Social Intelligence in the Age of LLMs](https://aclanthology.org/2025.naacl-tutorial.8/) (Zhu et al., NAACL 2025)
ACL
- Hao Zhu, Bodhisattwa Prasad Majumder, Dirk Hovy, and Diyi Yang. 2025. Social Intelligence in the Age of LLMs. In Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts), pages 51–55, Albuquerque, New Mexico. Association for Computational Linguistics.