README updated.

README.md

@@ -4,14 +4,22 @@ The flex-nlp package consists of a set of tools and utilities to work with Natur
 
 flex-nlp comes with some tools to work with NLP datasets, such as sampling and collating. It also provides tools to adapt external datasets to the FLEXible framework, like the Triplet Dataset tipically used in Sentence Similarity tasks.
 
-## Tutorials
+##  Tutorials
 
 To get started with flex-nlp, you can check the [notebooks](https://github.com/FLEXible-FL/flex-nlp/tree/main/notebooks) available in the repository. They cover the following topics:
 
 - [Sentiment Analysis using the IMDB dataset with a BiGRU model](https://github.com/FLEXible-FL/flex-nlp/blob/main/notebooks/Federated%20IMDb%20PT%20using%20FLExible%20with%20a%20GRU.ipynb).
 - [Question Answering using the SQuAD dataset with DistilBERT model](https://github.com/FLEXible-FL/flex-nlp/blob/main/notebooks/Federated%20QA%20with%20Hugginface%20using%20FLEXIBLE.ipynb).
 - [Semantic Textual Similarity using the QQP-Triplets dataset with a distilled version of Roberta](https://github.com/FLEXible-FL/flex-nlp/blob/main/notebooks/Federated%20SS%20with%20SentenceTransformers%20using%20FLEXible.ipynb).
 
+In the following we detail the tasks and the datasets used in the notebooks:
+
+| `Task`            | `Model`      | `Dataset`              |
+| ------------------ | ------------------ | ------------------- |
+| Sentiment Analysis | [BiGRU](https://arxiv.org/abs/1412.3555) | [IMDb](https://ai.stanford.edu/~amaas/data/sentiment/) |
+| Question Answering | [DistilBERT](https://arxiv.org/abs/1910.01108) | [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) |
+| Semantic Textual Similarity | [DistilRoberta](https://arxiv.org/abs/1907.11692) | [QQP-Triplets](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs) |
+
 ## Installation
 
 We recommend Anaconda/Miniconda as the package manager. The following is the corresponding `flex-nlp` versions and supported Python versions.