arXiv AI
Jul 14
Comparative Analysis of GAT and BERT for Human-Like Playtesting
arXiv:2607. 11501v1 Announce Type: new Abstract: Accurately modeling and understanding player experience is crucial for designing engaging puzzle games.
Comparative Analysis of GAT and BERT for Human-Like Playtesting
Accurately modeling and understanding player experience is crucial for designing engaging puzzle games. To achieve this, a common approach involves collecting diverse user data to train predictive playtesting models that mimic player behavior.
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arXiv AI
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CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations
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arXiv AI
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Play Like Champions: Counterfactual Feedback Generation in Latent Space
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arXiv Computer Vision
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arXiv AI
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EXPLORE-Bench: Egocentric Scene Prediction with Long-Horizon Reasoning
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arXiv Computer Vision
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SportsGrounder: Proposal-Aided Interleaved Grounding for Dense Sports Video Reasoning
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arXiv Computation and Language
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arXiv AI
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A Universal Dense Football Event Representation Based on TabTransformer
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arXiv AI
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