4 papers
Can Large Language Models Capture Video Game Engagement?
David Melhart, Matthew Barthet, Georgios N. Yannakakis
Can out-of-the-box pretrained Large Language Models (LLMs) detect human affect successfully when observing a video? To address this question, for the first time, we evaluate compre…
Emotions as Ambiguity-aware Ordinal Representations
Jingyao Wu, Matthew Barthet, David Melhart +1
Emotions are inherently ambiguous and dynamic phenomena, yet existing continuous emotion recognition approaches either ignore their ambiguity or treat ambiguity as an independent a…
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…
The Procedural Content Generation Benchmark: An Open-source Testbed for Generative Challenges in Games
Ahmed Khalifa, Roberto Gallotta, Matthew Barthet +3
This paper introduces the Procedural Content Generation Benchmark for evaluating generative algorithms on different game content creation tasks. The benchmark comes with 12 game-re…