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20212026
most citedLarge Language Models and Games: A Survey and Roadmap

122 citations · 172 across the 11 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.AI2024

Affectively Framework: Towards Human-like Affect-Based Agents

Matthew Barthet, Roberto Gallotta, Ahmed Khalifa +2

Game environments offer a unique opportunity for training virtual agents due to their interactive nature, which provides diverse play traces and affect labels. Despite their potent…

cs.HC2024★ 11 cited

GameVibe: A Multimodal Affective Game Corpus

Matthew Barthet, Maria Kaselimi, Kosmas Pinitas +3

As online video and streaming platforms continue to grow, affective computing research has undergone a shift towards more complex studies involving multiple modalities. However, th…

cs.NE2024

Dynamic Quality-Diversity Search

Roberto Gallotta, Antonios Liapis, Georgios N. Yannakakis

Evolutionary search via the quality-diversity (QD) paradigm can discover highly performing solutions in different behavioural niches, showing considerable potential in complex real…

cs.NE2024★ 2 cited

MAP-Elites with Transverse Assessment for Multimodal Problems in Creative Domains

Marvin Zammit, Antonios Liapis, Georgios N. Yannakakis

The recent advances in language-based generative models have paved the way for the orchestration of multiple generators of different artefact types (text, image, audio, etc.) into…

cs.CL2024★ 122 cited

Large Language Models and Games: A Survey and Roadmap

Roberto Gallotta, Graham Todd, Marvin Zammit +4

Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic. While starting as a niche area within nat…

cs.CV2024

BehAVE: Behaviour Alignment of Video Game Encodings

Nemanja Rašajski, Chintan Trivedi, Konstantinos Makantasis +2

Domain randomisation enhances the transferability of vision models across visually distinct domains with similar content. However, current methods heavily depend on intricate simul…