Update README.md

README.md

@@ -22,19 +22,19 @@ We release [InterpretMe]
 *Ruth C Fong and Andrea Vedaldi.*.CVPR 2017. [paper]
 
 1. **Supervised topic models for clinical interpretability.**
-*Michael C Hughes, Huseyin Melih Elibol, Thomas McCoy, Roy Perlis, and Finale Doshi-Velez.*.2016. [paper](https://arxiv.org/pdf/1612.01678)
+*Michael C Hughes, Huseyin Melih Elibol, Thomas McCoy, Roy Perlis, and Finale Doshi-Velez*.2016. [paper](https://arxiv.org/pdf/1612.01678)
 
 1. **A unified approach to interpreting model predictions.**
-*Scott Lundberg and Su-In Lee.*.2016. [paper](https://arxiv.org/pdf/1705.07874)
+*Scott Lundberg and Su-In Lee*.2016. [paper](https://arxiv.org/pdf/1705.07874)
  
 1. **A human-grounded evaluation benchmark for local explanations of machine learning.**
-*Sina Mohseni and Eric D Ragan.*.2018. [paper](https://arxiv.org/pdf/1801.05075).
+*Sina Mohseni and Eric D Ragan*.2018. [paper](https://arxiv.org/pdf/1801.05075).
 
 1. **Anchors: High-precision model-agnostic explanations.**
-*Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin.*.AAAI 2018. [paper]
+*Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin*.AAAI 2018. [paper]
 
 1. **Right for the right reasons: Training differentiable models by constraining their explanations.**
-*Andrew Slavin Ross, Michael C. Hughes, and Finale Doshi-Velez.*.IJCAI 2018. [paper](https://doi.org/10.24963/ijcai.2017/371)
+*Andrew Slavin Ross, Michael C. Hughes, and Finale Doshi-Velez*.IJCAI 2018. [paper](https://doi.org/10.24963/ijcai.2017/371)
 
 1. **Sharing Deep Neural Network Models with Interpretation.**
 *Huijun Wu, Chen Wang, Jie Yin, Kai Lu and Liming Zhu*. WWW’18.  [paper](https://doi.org/10.24963/ijcai.2017/371)