Update table of contents

README.md

@@ -7,16 +7,16 @@ Members of the project:
 - Mira Umlauf [umlauf@cl.uni-heidelberg.de](mailto:umlauf@cl.uni-heidelberg.de)
 
 # Table of contents
-1. 📚 [Project documents](#documents)
+1. 📚 [Project documents](#project-documents)
 2. 🔎 [Metonomy Resolution](#metonomy)
-3. 📈 [Data Augmentation](#augmentation)
+3. 📈 [Data Augmentation](#data-augmentation)
 4. 💡 [Methods](#methods)
     1. 📝 [Backtranslation](#backtranslation)
     2. 🍸 [MixUp](#mixup)
 5. 🗃️ [Data](#data)
-6. 🛠️ [Set Up](#setup)
+6. 🛠️ [Set Up](#set-up)
 7. ⚙️ [Usage](#usage)
-8. 🏯 [Code Structure](#structure)
+8. 🏯 [Code Structure](#code-structure)
 9. 📑 [References](#references)
 
 ***
@@ -221,10 +221,15 @@ For `<COMMAND>` you must enter one of the commands you find in the list below, w
     - [Downloaded TWM datasets](./swp/swp-data-augmentation-for-metonymy-resolution/datasets/li_twm)
 
 [^1]: Fairseq Tool.
+
 [^2]: Backtranslation paper.
+
 [^3]: Zhang, Hongyi, Cissé, Moustapha, Dauphin, Yann N. & Lopez-Paz, David. mixup: Beyond empirical risk minimization. *CoRR*, 2017.
+
 [^4]: Sun, L., Xia, C., Yin, W., Liang, T., Yu, P. S., & He, L. (2020). Mixup-transformer: dynamic data augmentation for NLP tasks. arXiv preprint arXiv:2010.02394.
-[^5]: Li et al.
+
+[^5]: Li, Haonan, Vasardani, Maria, Tomko, Martin & Baldwin, Timothy. ["Target word masking for location metonymy resolution."](https://aclanthology.org/2020) Proceedings of the 28th International Conference on Computational Linguistics, December 2020.
+
 [^6]: Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.
 [^7]: Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.