# In Search for Linear Relations in Sentence Embedding Spaces

arXiv: https://arxiv.org/abs/1910.03375 · HTML: https://mlsanity.com/paper/1910.03375/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Oct 2019.

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

- [Just Rank: Rethinking Evaluation with Word and Sentence Similarities](https://mlsanity.com/paper/2203.02679/) (2022)
- [Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings](https://mlsanity.com/paper/2301.08998/) (2023)
- [Semantic Composition in Visually Grounded Language Models](https://mlsanity.com/paper/2305.16328/) (2023)

## Abstract (arXiv)

We present an introductory investigation into continuous-space vector representations of sentences. We acquire pairs of very similar sentences differing only by a small alterations (such as change of a noun, adding an adjective, noun or punctuation) from datasets for natural language inference using a simple pattern method. We look into how such a small change within the sentence text affects its representation in the continuous space and how such alterations are reflected by some of the popular sentence embedding models. We found that vector differences of some embeddings actually reflect small changes within a sentence.