Towards a fuller understanding of neurons with Clustered Compositional Explanations

Autor:	La Rosa, Biagio, Gilpin, Leilani H., Capobianco, Roberto
Rok vydání:	2023
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Compositional Explanations is a method for identifying logical formulas of concepts that approximate the neurons' behavior. However, these explanations are linked to the small spectrum of neuron activations (i.e., the highest ones) used to check the alignment, thus lacking completeness. In this paper, we propose a generalization, called Clustered Compositional Explanations, that combines Compositional Explanations with clustering and a novel search heuristic to approximate a broader spectrum of the neurons' behavior. We define and address the problems connected to the application of these methods to multiple ranges of activations, analyze the insights retrievable by using our algorithm, and propose desiderata qualities that can be used to study the explanations returned by different algorithms. Comment: Accepted at NeurIPS 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.18443 Zobrazit plný text záznamu View this record from Arxiv