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@@ -4,10 +4,10 @@ This repository contains spike-encoded features of the [CIFAR-10 dataset](https:
 
 Spike features were extracted in an unsupervised fashion by a Convolutional Spiking Neural Network (CSNN) trained with Spike Timing-Dependent Plasticity (STDP).
 
-These features have been used in the following paper: *Gaspard Goupy, Pierre Tirilly, and Ioan Marius Bilasco. Neuronal Competition Groups with Supervised STDP for Spike-Based Classification. Advances in Neural Information Processing Systems, 38, 2024*.
+These features have been used for training spiking classification layers, as described in the following paper: *Gaspard Goupy, Pierre Tirilly, and Ioan Marius Bilasco. Neuronal Competition Groups with Supervised STDP for Spike-Based Classification. Advances in Neural Information Processing Systems, 38, 2024*.
 
 The official code for the paper is available [here](https://gitlab.univ-lille.fr/fox/snn-ncg/). 
 
-You can extract these features yourself, as well as those for the MNIST, Fashion-MNIST and CIFAR-100 datasets, by following the instructions in the official repository. However, we provide these features to facilitate quick experimentation with code of the paper.
+You can extract these features yourself, as well as those for the MNIST, Fashion-MNIST and CIFAR-100 datasets, by following the instructions in the official code repository. However, we provide these features to facilitate quick experimentation with the code.
 
 Please see the code repository and the paper for additional information.
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