Added better FASTopic docs

Author: x-tabdeveloping

docs/FASTopic.md

@@ -1,14 +1,59 @@
 # FASTopic
 
-FASTopic is a neural topic model based on Dual Semantic-relation Reconstruction.
+FASTopic (Wu et al., 2024) is a neural topic model based on Dual Semantic-relation Reconstruction.
 
-> Turftopic contains an implementation repurposed for our API, but the implementation is mostly from the [original FASTopic package](https://github.com/BobXWu/FASTopic).
+<figure>
+  <img src="../images/fastopic.png", title="", style="width:1050px;padding:0px;border:none;"></img>
+  <figcaption> Figure 1: Schematic Overview of the FASTopic Model.<br> <i>Figure from Wu et al. (2024)</i> </figcaption>
+</figure>
 
-:warning: This part of the documentation is still under construction :warning:
+FASTopic, instead of reconstructing Bag-of-words, like classical topic models or VAE-based models do, reconstructs the relations between topics words and documents.
+
+Wu et al. (2025) express semantic relations for this model using the Embedding Transport Plan (ETP) method.
+
+The model uses a combined loss function that helps the model learn semantic relations between topic and word embeddings, and learn to reconstruct these relations.
+
+## Usage
+
+```python
+from turftopic import FASTopic
+
+documents = [...]
+
+model = FASTopic(10)
+doc_topic_matrix = model.fit_transform(documents)
+model.print_topics()
+```
 
 ## References
 
-Wu, X., Nguyen, T., Zhang, D. C., Wang, W. Y., & Luu, A. T. (2024). FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm. ArXiv Preprint ArXiv:2405.17978.
+Please cite the authors of the paper, and  Turftopic when using the FASTopic model:
+
+```bibtex
+@inproceedings{
+  wu2024fastopic,
+  title={{FAST}opic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model},
+  author={Xiaobao Wu and Thong Thanh Nguyen and Delvin Ce Zhang and William Yang Wang and Anh Tuan Luu},
+  booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
+  year={2024},
+  url={https://openreview.net/forum?id=7t6aq0Fa9D}
+}
+
+@article{
+  Kardos2025,
+  title = {Turftopic: Topic Modelling with Contextual Representations from Sentence Transformers},
+  doi = {10.21105/joss.08183},
+  url = {https://doi.org/10.21105/joss.08183},
+  year = {2025},
+  publisher = {The Open Journal},
+  volume = {10},
+  number = {111},
+  pages = {8183},
+  author = {Kardos, Márton and Enevoldsen, Kenneth C. and Kostkan, Jan and Kristensen-McLachlan, Ross Deans and Rocca, Roberta},
+  journal = {Journal of Open Source Software} 
+}
+```
+
 
 ## API Reference