Abstract
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 un- derlying 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.- Anthology ID:
- 2023.cxgsnlp-1.3
- Volume:
- Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)
- Month:
- March
- Year:
- 2023
- Address:
- Washington, D.C.
- Venues:
- CxGsNLP | SyntaxFest
- SIG:
- SIGPARSE
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 21–30
- Language:
- URL:
- https://aclanthology.org/2023.cxgsnlp-1.3
- DOI:
- Cite (ACL):
- Ludovica Pannitto and Aurélie Herbelot. 2023. CALaMo: a Constructionist Assessment of Language Models. In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), pages 21–30, Washington, D.C.. Association for Computational Linguistics.
- Cite (Informal):
- CALaMo: a Constructionist Assessment of Language Models (Pannitto & Herbelot, CxGsNLP-SyntaxFest 2023)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2023.cxgsnlp-1.3.pdf