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Found 4 papers, 1 papers with code
EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations
Explanations in interactive machine-learning systems facilitate debugging and improving prediction models.
Lessons Learned from EXMOS User Studies: A Technical Report Summarizing Key Takeaways from User Studies Conducted to Evaluate The EXMOS Platform
Our research involved a comprehensive examination of the impact of global explanations rooted in both data-centric and model-centric perspectives within systems designed to support healthcare experts in optimising machine learning models through both automated and manual data configurations.
Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations
Results indicate that our participants preferred our representation of data-centric explanations that provide local explanations with a global overview over other methods.
Empirical Analysis of Image Caption Generation using Deep Learning
Automated image captioning is one of the applications of Deep Learning which involves fusion of work done in computer vision and natural language processing, and it is typically performed using Encoder-Decoder architectures.
