# Intuitive Contrasting Map for Antonym Embeddings

arXiv: https://arxiv.org/abs/2004.12835 · HTML: https://mlsanity.com/paper/2004.12835/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [Does Visual Grounding Enhance the Understanding of Embodied Knowledge in Large Language Models?](https://mlsanity.com/paper/2510.16924/) (2025)
- [A visual observation on the geometry of UMAP projections of the difference vectors of antonym and synonym word pair embeddings](https://mlsanity.com/paper/2603.24150/) (2026)

## Abstract (arXiv)

This paper shows that, modern word embeddings contain information that distinguishes synonyms and antonyms despite small cosine similarities between corresponding vectors. This information is encoded in the geometry of the embeddings and could be extracted with a straight-forward and intuitive manifold learning procedure or a contrasting map. Such a map is trained on a small labeled subset of the data and can produce new embeddings that explicitly highlight specific semantic attributes of the word. The new embeddings produced by the map are shown to improve the performance on downstream tasks.