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Found 5 papers, 1 papers with code
On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis
A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would help answer the question of what a deep learning system internally detects as relevant in the input, demystifying the otherwise black-box nature of deep learning systems.
Concept Induction using LLMs: a user experiment for assessment
To evaluate the output, we compare the concepts generated by the LLM with two other methods: concepts generated by humans and the ECII heuristic concept induction system.
Common Sense Reasoning
Explainable artificial intelligence
+4
On the Psychology of GPT-4: Moderately anxious, slightly masculine, honest, and humble
We subject GPT-4 to a number of rigorous psychometric tests and analyze the results.
Understanding CNN Hidden Neuron Activations Using Structured Background Knowledge and Deductive Reasoning
A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would provide insights into the question of what a deep learning system has internally detected as relevant on the input, demystifying the otherwise black-box character of deep learning systems.
Explaining Deep Learning Hidden Neuron Activations using Concept Induction
One of the current key challenges in Explainable AI is in correctly interpreting activations of hidden neurons.
