Pith. sign in

REVIEW 2 cited by

GPT for Games: A Scoping Review (2020-2023)

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2404.17794 v1 pith:WTVRGP7Z submitted 2024-04-27 cs.HC cs.AI

Daijin Yang , Erica Kleinman , Casper Harteveld This is my paper · ORCID
classification cs.HCcs.AI
keywords gamegamesapplicationsresearchreviewareascurrentmixed-initiative
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

This paper introduces a scoping review of 55 articles to explore GPT's potential for games, offering researchers a comprehensive understanding of the current applications and identifying both emerging trends and unexplored areas. We identify five key applications of GPT in current game research: procedural content generation, mixed-initiative game design, mixed-initiative gameplay, playing games, and game user research. Drawing from insights in each of these application areas, we propose directions for future research in each one. This review aims to lay the groundwork by illustrating the state of the art for innovative GPT applications in games, promising to enrich game development and enhance player experiences with cutting-edge AI innovations.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. MoGraphGPT: Creating Interactive Scenes Using Modular LLM and Graphical Control

    cs.HC 2025-02 conditional novelty 6.0 of 10

    An interactive no-code system combining element-level modular LLM sessions, drawing-based graphical proxies, and automatic sliders creates 2D scenes faster than Cursor Composer in a 10-participant study.

  2. Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs

    cs.AI 2025-09 reject novelty 4.0 of 10

    Fine-tuning LLaMA-3 on GPT-4-generated GDD-code pairs yields a model that writes Unity C# templates from game design documents, but the reported 4.8/5.0 advantage over baselines rests on a weak three-game, three-rater...

Pith tools