# A case for deep learning in semantics

arXiv: https://arxiv.org/abs/1809.03068 · HTML: https://mlsanity.com/paper/1809.03068/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2018.

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

- [From partners to populations: A hierarchical Bayesian account of coordination and convention](https://mlsanity.com/paper/2104.05857/) (2021)
- [On the Compatibility of Generative AI and Generative Linguistics](https://mlsanity.com/paper/2411.10533/) (2024)

## Abstract (arXiv)

Pater's target article builds a persuasive case for establishing stronger ties between theoretical linguistics and connectionism (deep learning). This commentary extends his arguments to semantics, focusing in particular on issues of learning, compositionality, and lexical meaning.