@inproceedings{liu-etal-2026-review,
title = "A Review of Incorporating Psychological Theories in {LLM}s",
author = "Liu, Zizhou and
Gong, Ziwei and
Ai, Lin and
Hui, Zheng and
Chen, Run and
Leach, Colin Wayne and
Greene, Michelle R. and
Hirschberg, Julia",
editor = "Demberg, Vera and
Inui, Kentaro and
Marquez, Llu{\'i}s",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = mar,
year = "2026",
address = "Rabat, Morocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-long.350/",
pages = "7459--7495",
ISBN = "979-8-89176-380-7",
abstract = "Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop, there is a rising consensus that psychology is essential for capturing human-like cognition, behavior, and interaction.This paper reviews how psychological theories can inform and enhance stages of LLM development. Our review integrates insights from six subfields of psychology, including cognitive, developmental, behavioral, social, personality psychology, and psycholinguistics. With stage-wise analysis, we highlight current trends and gaps in how psychological theories are applied. By examining both cross-domain connections and points of tension, we aim to bridge disciplinary divides and promote more thoughtful integration of psychology into NLP research."
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%0 Conference Proceedings
%T A Review of Incorporating Psychological Theories in LLMs
%A Liu, Zizhou
%A Gong, Ziwei
%A Ai, Lin
%A Hui, Zheng
%A Chen, Run
%A Leach, Colin Wayne
%A Greene, Michelle R.
%A Hirschberg, Julia
%Y Demberg, Vera
%Y Inui, Kentaro
%Y Marquez, Lluís
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-380-7
%F liu-etal-2026-review
%X Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop, there is a rising consensus that psychology is essential for capturing human-like cognition, behavior, and interaction.This paper reviews how psychological theories can inform and enhance stages of LLM development. Our review integrates insights from six subfields of psychology, including cognitive, developmental, behavioral, social, personality psychology, and psycholinguistics. With stage-wise analysis, we highlight current trends and gaps in how psychological theories are applied. By examining both cross-domain connections and points of tension, we aim to bridge disciplinary divides and promote more thoughtful integration of psychology into NLP research.
%U https://aclanthology.org/2026.eacl-long.350/
%P 7459-7495
Markdown (Informal)
[A Review of Incorporating Psychological Theories in LLMs](https://aclanthology.org/2026.eacl-long.350/) (Liu et al., EACL 2026)
ACL
- Zizhou Liu, Ziwei Gong, Lin Ai, Zheng Hui, Run Chen, Colin Wayne Leach, Michelle R. Greene, and Julia Hirschberg. 2026. A Review of Incorporating Psychological Theories in LLMs. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7459–7495, Rabat, Morocco. Association for Computational Linguistics.