Modelling Language using Large Language Models
Not on the map. Why?
Abstract (arXiv)
This paper argues that large language models have a valuable scientific role to play in serving as scientific models of public languages. Linguistic study should not only be concerned with the cognitive processes behind linguistic competence, but also with language understood as an external, social entity. Once this is recognized, the value of large language models as scientific models becomes clear. This paper defends the position against a number of arguments to the effect that language models provide no linguistic insight. Building upon Weisberg's (2007) notion of a model construal, it is then argued that recent work in computational linguistics to better understand the inner workings of large language models can be used to develop a model construal for large language models as models of a language.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 10 of its 47 references that are in the map. First posted on arXiv 15 Apr 2024.
Builds on
10 of 47 references.
References · 10
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,718
- 2020A Primer in BERTology: What we know about how BERT workscited by 807
- 2023Language models are not naysayers: An analysis of language models on negation benchmarkscited by 73
- 2021On the proper role of linguistically-oriented deep net analysis in linguistic theorizingcited by 43
- 2021Dodrio: Exploring Transformer Models with Interactive Visualizationcited by 28
- 2020Contextualized Word Embeddings Encode Aspects of Human-Like Word Sense Knowledgecited by 18
Built on by
Citing papers per year: 2024: 1; 2025: 1.
2 papers.