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Found 6 papers, 3 papers with code
Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting
This classifier is then used to detect if a trained model is overfit.
GlitchBench: Can large multimodal models detect video game glitches?
To address this gap, we introduce GlitchBench, a novel benchmark derived from video game quality assurance tasks, to test and evaluate the reasoning capabilities of LMMs.
Large Language Models are Pretty Good Zero-Shot Video Game Bug Detectors
As a result, it is challenging to fully automate game testing.
CLIP meets GamePhysics: Towards bug identification in gameplay videos using zero-shot transfer learning
Our approach does not rely on any external information (such as video metadata); it works solely based on the content of the video.
Studying Popular Open Source Machine Learning Libraries and Their Cross-Ecosystem Bindings
Our study shows that the vast majority of the studied bindings cover only a small portion of the source library releases, and the delay for receiving support for a source library release is large.
Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Review
The goal of this review paper is to analyze and summarize: (1) which anomaly detection techniques can benefit from certain types of GANs, and how, (2) in which application domains GAN-assisted anomaly detection techniques have been applied, and (3) which datasets and performance metrics have been used to evaluate these techniques.
