Update README.md

README.md

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-license: mit
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-
+---
+license: mit
+datasets:
+- ILSVRC/imagenet-1k
+tags:
+- uncertainty quantification
+- model robustness
+- selective classification
+- label-smoothing
+---
+
+[![arXiv](https://img.shields.io/badge/arXiv-2403.14715-b31b1b.svg)](https://arxiv.org/abs/2403.14715)
+
+This repository contains the models trained as experimental support for the paper "Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It" published at ICLR.
+
+The code is based on [TorchUncertainty](https://github.com/ENSTA-U2IS-AI/torch-uncertainty) and available on [GitHub](https://github.com/o-laurent/Label-smoothing-Selective-classification).
+
+## List of models
+
+This repository contains:
+- for segmentation: one CE-based and one LS-based (LS coefficient 0.2) DeepLabv3+ Resnet-101 
+- for nlp: one CE-based and LS-based one (LS coefficient 0.6) LSTM-MLP
+
+The rest of the models (notably on tabular data) used in the paper are trainable on CPU in the dedicated notebooks.