21 citations · 32 across the 12 of their papers we have counts for
4 papers · 1 filter
A novel post-hoc explanation comparison metric and applications
Shreyan Mitra, Leilani Gilpin
Explanatory systems make the behavior of machine learning models more transparent, but are often inconsistent. To quantify the differences between explanatory systems, this paper p…
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa, Leilani H. Gilpin, Roberto Capobianco
Compositional Explanations is a method for identifying logical formulas of concepts that approximate the neurons' behavior. However, these explanations are linked to the small spec…
Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations
Shiyuan Huang, Siddarth Mamidanna, Shreedhar Jangam +2
Large language models (LLMs) such as ChatGPT have demonstrated superior performance on a variety of natural language processing (NLP) tasks including sentiment analysis, mathematic…
Convolutional Neural Network Model for Diabetic Retinopathy Feature Extraction and Classification
Sharan Subramanian, Leilani H. Gilpin
The application of Artificial Intelligence in the medical market brings up increasing concerns but aids in more timely diagnosis of silent progressing diseases like Diabetic Retino…