# Is it the end of (generative) linguistics as we know it?

arXiv: https://arxiv.org/abs/2412.12797 · HTML: https://mlsanity.com/paper/2412.12797/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 98 references that are in the map.
- First posted on arXiv 17 Dec 2024.

## Builds on (most cited first, 12 of 12)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Scaling Laws for Neural Language Models](https://mlsanity.com/paper/2001.08361/) (2020)
- [Neural Network Acceptability Judgments](https://mlsanity.com/paper/1805.12471/) (2018)
- [BLiMP: The Benchmark of Linguistic Minimal Pairs for English](https://mlsanity.com/paper/1912.00582/) (2019)
- [Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies](https://mlsanity.com/paper/1611.01368/) (2016)
- [A Systematic Assessment of Syntactic Generalization in Neural Language Models](https://mlsanity.com/paper/2005.03692/) (2020)
- [When Do You Need Billions of Words of Pretraining Data?](https://mlsanity.com/paper/2011.04946/) (2020)
- [What do RNN Language Models Learn about Filler-Gap Dependencies?](https://mlsanity.com/paper/1809.00042/) (2018)
- [Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus](https://mlsanity.com/paper/2109.12053/) (2021)
- [Language learning from positive evidence, reconsidered: A simplicity-based approach](https://mlsanity.com/paper/1301.4432/) (2013)
- [Expectation-based Minimalist Grammars](https://mlsanity.com/paper/2109.13871/) (2021)

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

- [Generative Linguistics, Large Language Models, and the Social Nature of Scientific Success](https://mlsanity.com/paper/2503.20088/) (2025)
- [Tracing the ongoing emergence of human-like reasoning in Large Language Models](https://mlsanity.com/paper/2605.21299/) (2026)

## Abstract (arXiv)

A significant debate has emerged in response to a paper written by Steven Piantadosi (Piantadosi, 2023) and uploaded to the LingBuzz platform, the open archive for generative linguistics. Piantadosi's dismissal of Chomsky's approach is ruthless, but generative linguists deserve it. In this paper, I will adopt three idealized perspectives -- computational, theoretical, and experimental -- to focus on two fundamental issues that lend partial support to Piantadosi's critique: (a) the evidence challenging the Poverty of Stimulus (PoS) hypothesis and (b) the notion of simplicity as conceived within mainstream Minimalism. In conclusion, I argue that, to reclaim a central role in language studies, generative linguistics -- representing a prototypical theoretical perspective on language -- needs a serious update leading to (i) more precise, consistent, and complete formalizations of foundational intuitions and (ii) the establishment and utilization of a standardized dataset of crucial empirical evidence to evaluate the theory's adequacy. On the other hand, ignoring the formal perspective leads to major drawbacks in both computational and experimental approaches. Neither descriptive nor explanatory adequacy can be easily achieved without the precise formulation of general principles that can be challenged empirically.