# CALaMo: a Constructionist Assessment of Language Models

arXiv: https://arxiv.org/abs/2302.03589 · HTML: https://mlsanity.com/paper/2302.03589/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 36 references that are in the map.
- First posted on arXiv 7 Feb 2023.

## Builds on (most cited first, 1 of 1)

- [Recurrent babbling: evaluating the acquisition of grammar from limited input data](https://mlsanity.com/paper/2010.04637/) (2020)

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

- [Construction Identification and Disambiguation Using BERT: A Case Study of NPN](https://mlsanity.com/paper/2503.18751/) (2025)
- ['Layer su Layer': Identifying and Disambiguating the Italian NPN Construction in BERT's family](https://mlsanity.com/paper/2604.03673/) (2026)

## Abstract (arXiv)

This paper presents a novel framework for evaluating Neural Language Models' linguistic abilities using a constructionist approach. Not only is the usage-based model in line with the underlying stochastic philosophy of neural architectures, but it also allows the linguist to keep meaning as a determinant factor in the analysis. We outline the framework and present two possible scenarios for its application.