# Going Beyond T-SNE: Exposing textttwhatlies in Text Embeddings

arXiv: https://arxiv.org/abs/2009.02113 · HTML: https://mlsanity.com/paper/2009.02113/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Sep 2020.

## Built on by (most cited first, 3 of 3)

- [Semi-supervised Interactive Intent Labeling](https://mlsanity.com/paper/2104.13406/) (2021)
- [SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks](https://mlsanity.com/paper/2305.03039/) (2023)
- [TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora](https://mlsanity.com/paper/2103.11029/) (2021)

## Abstract (arXiv)

We introduce whatlies, an open source toolkit for visually inspecting word and sentence embeddings. The project offers a unified and extensible API with current support for a range of popular embedding backends including spaCy, tfhub, huggingface transformers, gensim, fastText and BytePair embeddings. The package combines a domain specific language for vector arithmetic with visualisation tools that make exploring word embeddings more intuitive and concise. It offers support for many popular dimensionality reduction techniques as well as many interactive visualisations that can either be statically exported or shared via Jupyter notebooks. The project documentation is available from https://rasahq.github.io/whatlies/.