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A Review of Incorporating Psychological Theories in LLMs

Paper · 2026 · Zizhou Liu, Ziwei Gong, Lin Ai et al.

Summary

LLM research often borrows ideas from psychology, but earlier surveys cover the link only in part. They treat LLMs as instruments for psychologists, as subjects of psychological testing, or as systems improved by one chosen construct. Liu et al. try instead to map the whole model lifecycle. They classify 227 papers by six branches of psychology (cognitive, developmental, behavioral, social, personality, psycholinguistics) and by four development stages (preprocessing, pre-training, post-training, evaluation/application). For each stage they show which theories have been used:

  • Data construction: ecological validity and child-directed speech.
  • Pre-training: Piagetian development and scaffolding, as analogies for curriculum-style training.
  • RLHF: operant conditioning.
  • Assessment: ToM, conformity, and Big Five tests.

The authors also point out gaps and open disputes, such as whether simulated personas are stable or prompt-dependent. They warn against reading human cognition into models from surface similarities. The survey matters as an interdisciplinary bridge and as a call for careful construct validity whenever human theories are transferred to LLMs.

Key points

  • The 227 surveyed papers come from NeurIPS, ICML, ICLR, COLING, and major *CL venues, along with arXiv preprints that have been influential.
  • The taxonomy (Figure 1) is colour-coded by subfield. Examples include selective attention and predictive coding for data filtering, working memory for pre-training, and Thorndike's Law of Effect for RLHF.
  • Evaluation work relies heavily on ToM benchmarks, Big Five, MBTI, and EPQR-A personality instruments, plus social identity and conformity theories.
  • Multi-agent and application work draws on dual-process theory, self-reflection, and persuasion models.
  • On ethics, the authors flag manipulative reinforcement schedules, WEIRD sampling bias, and psychology's individual-level focus. They recommend complementing it with linguistics, sociology, and HCI.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓Columbia UniversityNew York · United States241 works · 54,053 citations🎓University of CambridgeCambridge · United Kingdom243 works · 121,396 citations🎓Barnard CollegeNew York · United States4 works · 199 citations

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 3,320 works

Cite

Cite as 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. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.eacl-long.350

@inproceedings{liu2026review,
  title = {{A Review of Incorporating Psychological Theories in LLMs}},
  author = {Zizhou Liu, Ziwei Gong, Lin Ai, Zheng Hui, Run Chen, Colin Wayne Leach, Michelle R. Greene and Julia Hirschberg},
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.eacl-long.350},
  url = {https://doi.org/10.18653/v1/2026.eacl-long.350}
}

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