citation

README.md

@@ -4,7 +4,7 @@
 
 This project is about explaining what machine learning classifiers (or models) are doing.
 At the moment, we support explaining individual predictions for text classifiers or classifiers that act on tables (numpy arrays of numerical or categorical data) or images, with a package called lime (short for local interpretable model-agnostic explanations).
-Lime is based on the work presented in [this paper](https://arxiv.org/abs/1602.04938). Here is a link to the promo video:
+Lime is based on the work presented in [this paper](https://arxiv.org/abs/1602.04938) ([bibtex here for citation](https://github.com/marcotcr/lime/blob/master/citation.bib)). Here is a link to the promo video:
 
 <a href="https://www.youtube.com/watch?v=hUnRCxnydCc" target="_blank"><img src="https://raw.githubusercontent.com/marcotcr/lime/master/doc/images/video_screenshot.png" width="450" alt="KDD promo video"/></a>
 

citation.bib

@@ -0,0 +1,11 @@
+@inproceedings{lime,
+  author    = {Marco Tulio Ribeiro and
+               Sameer Singh and
+               Carlos Guestrin},
+  title     = {"Why Should {I} Trust You?": Explaining the Predictions of Any Classifier},
+  booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on
+               Knowledge Discovery and Data Mining, San Francisco, CA, USA, August
+               13-17, 2016},
+  pages     = {1135--1144},
+  year      = {2016},
+}